{"access":{"catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. 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Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n Staff FullStack Engineer, AI Acceleration Team\n The AI Acceleration Team\n The AI Acceleration Team builds AI features right where identity and agents meet. Companies are handing real access to AI agents faster than their controls can keep up, and two problems show up first: how do you authorize what an agent is allowed to do on someone's behalf, and how do you keep both people and agents from being phished? We take those on directly.\n Our North Star: to get AI right, you have to get identity right. We are a new team, and we shape the problems as much as we solve them. We bring a product mindset to the work: we dig into what customers actually need, define the outcome, and build toward it. We move fast, stay close to the real problem, and are honest about what works.\n The Staff FullStack Engineer Opportunity\n As a Staff FullStack Engineer on the AI Acceleration Team, you will own the technical build for solving agent authorization and phishing resistance. You see what needs doing and start it. This is 0-to-1 work, meaning you will move on problems before they are fully specified, always keeping customer success as the ultimate bar.\n You will help shape which problems we take on, make architectural calls that outlive any single project, and set the technical bar for how we work. You will enforce least privilege for what agents can do and make phishing-resistant access the default. We build with Vercel and AWS, and you will likely work heavily in JavaScript/TypeScript and Java.\n What you'll be doing\n \n Solve core authorization challenges: Define how companies authorize agent actions and enforce least privilege for what an agent can do on a user's behalf.\n Design secure access: Build phishing-resistant authentication and authorization for both people and the agents acting for them.\n Shape the product: Bring a product mindset to dig into what customers need, define the desired outcomes, and build toward them rather than just executing solutions.\n Own the quality bar: Act as the voice for product and quality judgment in the room, taking ownership of the outcome, not just the code.\n Drive technical architecture: Make and defend architectural decisions on distributed systems and complex API integrations that will scale as the work grows.\n Modernize development: Advance how we use AI across our development lifecycle—how we design, review, and ship—and bring the rest of the team along with you.\n Coach and multiply: Raise the technical bar of the entire team, building judgment in others rather than trying to solve everything yourself.\n Improve engineering excellence: Spot and prioritize tech debt, driving improvements beyond feature work (CI/CD, observability, documentation, reliability, and support).\n Stay customer-aware: Build with a clear, direct line to the customer problem and the outcome you're solving for, even if you aren't in every customer conversation.\n \n What you'll bring to the role\n \n A self-starter mentality: The ability to spot what matters, drive work autonomously, and thrive in ambiguity while helping to form a new charter.\n Advanced AI tool proficiency: The ability to apply AI meaningfully across the software development lifecycle, evaluate new tooling with good judgment, and establish practices for the wider team.\n Architectural expertise: Proven experience defining scalable backend architectures and integrating complex APIs with modern web technologies, including making decisions with lasting, org-wide impact.\n Security fundamentals: A solid grasp of web authentication and authorization, including how auth flows work and how to secure sensitive user data.\n Backend proficiency: Deep expertise in building reliable, secure, enterprise-grade software in Java or another type-safe language.\n Frontend flexibility: High proficiency in JavaScript/TypeScript with true fullstack range, including the ability to ship robust frontends.\n Cloud infrastructure knowledge: Strong cloud architecture fundamentals, with experience designing and operating large-scale services on AWS.\n \n Extra credit\n \n Background working on a zero-to-one, startup-like team.\n Track record of leading a team through a real shift in how they work (e.g., AI adoption, new developer tooling, or cultural shifts).\n Familiarity with developing Identity and Access Management (IAM) tooling.\n \n P25594\n Below is the annual salary range for candidates located in Canada. Your actual salary will depend on factors such as your skills, quali","salary_min":160000,"salary_max":220000,"location":"Toronto, Canada","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","healthcare","agents","cloud","fullstack"],"apply_url":"https://www.okta.com/company/careers/opportunity/8165163?gh_jid=8165163","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T23:31:40Z","expires_at":"2026-09-29T13:39:37.203584Z","created_at":"2026-08-29T13:40:17.175916Z","updated_at":"2026-08-30T13:39:37.341538Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/4a439361-6d5b-42c9-adff-208df6aad3bd"},{"id":"6e9d10aa-49d2-4e23-ba39-8a7c0475817b","company_id":"43dd17db-bec3-4ebb-a432-f71d57a9aa47","title":"Senior Data Scientist, CompBio","slug":"senior-data-scientist-compbio-d84439dd","description":"THE OPPORTUNITY\n\nState-of-the-art technologies that measure multiple cellular aspects of in vitro biology are at the heart of insitro's efforts to accelerate drug development. Computational biology is key to elucidating the relationship between these phenotypes and human disease and translating them into actionable outcomes.\n\nWe are looking for a computational biologist with expertise across diverse data modalities, including deep experience in either omics or imaging readouts, a strong understanding of cell and disease biology, and fluency with state-of-the-art analysis techniques. Your expertise will help the team navigate the complexities of identifying therapeutic targets from diverse data, elucidating biological mechanisms, and championing a culture of statistical rigor and experimental design to ensure our analyses meet the highest scientific standards.\n\nIn this role, you will directly impact target prioritization and drug development efforts, advance our understanding of diseases, and aid the development of new treatments. You will be part of a cross-functional team of life scientists, data scientists, bioengineers, software engineers, and machine learning scientists who strive to identify therapeutic targets and develop drugs of high efficacy and low toxicity. Based in South San Francisco, this position reports directly to the Head of Computational Biology and ML-Omics and offers an in-person hybrid schedule of three days per week.\n\nYou will be joining a vibrant biotech startup with many opportunities for significant impact. You will work closely with a highly talented team, learn a broad range of skills, and help shape insitro's culture, strategic direction, and outcomes. Join us, and help make a difference to patients!\n\n \n\n\nRESPONSIBILITIES\n\nMultimodal Analysis \u0026 Target Discovery\n\n - Synthesize Multimodal Insights: Draw insights from multimodal analyses (microscopy, spatial proteomics, bulk/single-cell RNA-seq, human cohort data) to uncover disease mechanisms and generate therapeutic hypotheses\n\n - Identify Therapeutic Targets: Analyze diverse data from disease-relevant in vitro models to identify potential therapeutic targets from perturbation screens\n\n - Discover Biomarkers: Analyze data from diverse sources to identify and validate potential biomarkers for monitoring disease status and progression\n\nExperimental Partnership\n\n - Partner on Experimental Design: Work with experimental biologists to design, troubleshoot, and optimize experiments that generate and validate mechanistic and therapeutic hypotheses\n\n - Provide Domain Expertise: Bring statistical and computational expertise to guide assay development and the biological interpretation of results\n\nAnalytical Rigor \u0026 Communication\n\n - Benchmark and Calibrate: Calibrate analysis tools and workflows, define performance metrics, and conduct benchmarking to select fit-for-purpose solutions\n\n - Communicate Findings: Share results with cross-functional stakeholders through reports, visualizations, presentations, and publications\n\n \n\n\nABOUT YOU\n\nExperience \u0026 Qualifications\n\n - Education \u0026 Tenure: Ph.D. in computational biology, systems biology, bioengineering, computer science, machine learning, or a related discipline, with 3+ years of working experience post-graduation\n\n - Data Modality Depth: Hands-on experience with diverse data modalities, including at least one of the following: single-cell RNA-seq, fluorescence microscopy, spatial proteomics or transcriptomics, or label-free microscopy\n\n - Statistical Foundation: Deep understanding of statistical modeling and data analysis, with a demonstrated ability to rigorously interpret complex datasets and generate mechanistic hypotheses\n\n - Biological Grounding: An understanding of molecular biology or disease biology (e.g., neurological, cardiovascular, or metabolic disorders)\n\n - Programming Skills: Strong programming ability and proficiency with Python scientific packages such as NumPy and pandas\n\n - Publication Record: Meaningful contributions to high-quality work published in relevant computational biology, systems biology, life sciences, or biomedical venues\n\nCore Competencies\n\n - Collaborative Communicator: You communicate effectively and collaborate well with people of diverse backgrounds and job functions\n\n - Engineering Discipline: You write well-commented code and documentation and are familiar with coding best practices such as version control and code review\n\n \n\n\nCOMPENSATION \u0026 BENEFITS AT INSITRO\n\nOur target starting salary for successful US-based applicants for this role is $183,000 - $194,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.\n\nThis role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) an","salary_min":183000,"salary_max":194000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["healthcare","payments","machine-learning","data-science"],"apply_url":"https://jobs.ashbyhq.com/insitro/ec4a278a-dd78-4e9c-a203-87e3e2f59e60/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T21:54:47.039Z","expires_at":"2026-09-29T13:36:50.193262Z","created_at":"2026-08-29T13:37:15.708222Z","updated_at":"2026-08-30T13:36:50.329078Z","company_name":"Insitro","company_slug":"insitro","company_logo_url":"https://www.google.com/s2/favicons?domain=insitro.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6e9d10aa-49d2-4e23-ba39-8a7c0475817b"},{"id":"ac9a7cfe-0d87-46a1-9a22-dc3d0f92e813","company_id":"12105b3e-eb1d-4a92-95b6-855042facaf1","title":"Senior Product Manager - Core AI (Understand)","slug":"senior-product-manager-core-ai-understand-795d69c4","description":"At Qualtrics, we create software the world’s best brands use to deliver exceptional frontline experiences, build high-performing teams, and design products people love. But we are more than a platform—we are the creators and stewards of the Experience Management category serving over 18K clients globally. Building a category takes grit, determination, and a disdain for convention—but most of all it requires close-knit, high-functioning teams with an unwavering dedication to serving our customers.\n When you join one of our teams, you’ll be part of a nimble group that’s empowered to set aggressive goals and move fast to achieve them. Strategic risks are encouraged and complex problems are solved together, by passing the mic and iterating until the best solution comes to light. You won’t have to look to find growth opportunities—ready or not, they’ll find you. From retail to government to healthcare, we’re on a mission to bring humanity, connection, and empathy back to business. Join over 5,000 people across the globe who think that’s work worth doing.\n Senior Product Manager, Core AI (Understand) \n Why We Have This Role \n \n Define the future of Qualtrics' Understand layer — the intelligence that turns raw experience data into structured meaning, prediction, and insight across the entire portfolio.\n Own the product strategy for the capabilities that let AI systems and product teams reason about experience data: ontologies and semantic systems, text analytics enrichments, prediction, simulation, and benchmarking.\n Own the Core AI platform foundations that these capabilities depend on: agent infrastructure, context and memory, tools and orchestration, agent evaluation, observability, and AI safety.\n Manage the entire lifecycle for multiple functional areas of Understand, from framing the problem, to aligning on architecture and product direction, to forming the plan, delivering implementation, and iterating until the capabilities are world-class.\n \n How You'll Find Success \n \n Partner with product, engineering, data science, research, and design teams across Qualtrics to understand what enrichment, modeling, and platform capabilities they need to build exceptional AI products.\n Develop a deep understanding of the needs of both enterprise customers and internal AI product builders, and translate those needs into strategy, requirements, and roadmaps.\n Define product strategy across the Understand surface area: ontologies and semantic layers, text analytics and enrichment pipelines, predictive models, simulation, benchmarking, and the agent runtime, orchestration, memory, evaluation, and guardrail capabilities that support them.\n Prioritize investments based on customer value, insight quality, developer productivity, technical leverage, reuse across Qualtrics products, and opportunities for competitive differentiation.\n Collaborate deeply with engineering, AI research, and data science teams to make thoughtful product and architectural tradeoffs in a rapidly evolving technical landscape.\n Develop clear frameworks for evaluating the quality, accuracy, reliability, safety, and business impact of enrichment models, predictive systems, and agentic AI.\n Build the benchmarking discipline that lets Qualtrics prove its models and enrichments are better than alternatives — internally and to customers.\n Create shared capabilities that accelerate AI development across Qualtrics while providing the reliability, governance, security, and observability required by enterprise customers.\n Develop and communicate a compelling vision and roadmap to senior leaders, product teams, technical stakeholders, and customers.\n Define and monitor meaningful KPIs for adoption, model and enrichment quality, prediction accuracy, evaluation performance, developer velocity, reliability, and customer impact.\n Stay at the forefront of developments in foundation models, agents, evaluation methods, semantic systems, causal and predictive modeling, simulation, and enterprise AI infrastructure — and translate them into concrete product opportunities.\n \n How You'll Grow \n \n By shaping the technical and product foundations for how Qualtrics understands experience data.\n Through developing deep expertise across ontologies, semantic systems, text analytics, prediction, simulation, benchmarking, agent architecture, and evaluation.\n By making high-leverage product decisions that influence multiple product lines and teams.\n Through leading complex, ambiguous initiatives that require alignment across product, engineering, research, data science, security, and go-to-market organizations.\n By developing your ability to connect rapidly evolving AI technologies to durable customer value and differentiated product strategy.\n \n Things You'll Do \n \n Develop and execute the product strategy for Qualtrics' Understand layer.\n Define the foundational architecture and capabilities required for teams across Qualtrics to build reliable, differentiat","salary_min":166500,"salary_max":218500,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","agents","generative-ai","nlp","alignment","healthcare"],"apply_url":"https://www.qualtrics.com/careers/us/en/job/8164973?gh_jid=8164973","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T21:33:55Z","expires_at":"2026-09-29T13:49:13.602802Z","created_at":"2026-08-29T13:50:43.963199Z","updated_at":"2026-08-30T13:49:13.735129Z","company_name":"Qualtrics","company_slug":"qualtrics","company_logo_url":"https://www.google.com/s2/favicons?domain=qualtrics.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ac9a7cfe-0d87-46a1-9a22-dc3d0f92e813"},{"id":"ef4c6406-333f-41ab-8184-e9bd7afe7c50","company_id":"a0000000-0000-0000-0000-000000000009","title":"Forward Deployed Engineer, Infrastructure Specialist (North America)","slug":"forward-deployed-engineer-infrastructure-specialist-north-america-85c940b9","description":"Who are we?\n\nCohere is the leading security-first enterprise AI company.  We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.\n\nWe’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.\n\nWe obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.\n\nWe are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!\n\n\nABOUT NORTH:\n\nNorth https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications.\n\n\n\n\nWHY THIS ROLE?\n\nThis role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications. Our esteemed clients include industry leaders like RBC, Dell, and LG CNS.\n\nWe are seeking engineers who deeply care about customers and want to work at the cutting edge of Agentic AI.\n\n\n\nIn this role, you will:\n\n - Lead end-to-end deployment of North in private cloud and on-premises environments, including planning, configuration, testing, and rollout.\n\n - Partner with enterprise IT teams to assess infrastructure, security requirements, and data management practices.\n\n - Experiment at a high velocity and with a high level of quality to engage our customers and ultimately deliver solutions that exceed their expectations\n\n - Design and implement deployment strategies tailored to client needs, ensuring compliance with data privacy and security standards.\n\n - Troubleshoot and resolve deployment-related technical issues, providing timely solutions to minimize downtime.\n\n\n\nYou may be a good fit if:\n\n - You have experience with and enjoy working directly with customers\n\n - You have experience deploying enterprise software in private/hybrid cloud environments\n\n - You have proven experience administering production Kubernetes clusters and expertise with Helm\n\n - Familiarity with DevOps practices, CI/CD pipelines, and tools like Git for version control\n\n - You have strong expertise in cloud infrastructure (Azure, AWS, GCP), networking, and virtualization\n\n - You excel in fast-paced environments and can execute while priorities and objectives are a moving target\n\nCohere is committed to fair and transparent pay practices. The salary range listed for this role reflects the expected base compensation. Actual compensation offered will be determined by factors such as location, level, job-related knowledge, skills, education, and experience.\n\n - United States:\n   \n   - For candidates based in California, New York and Washington States, the compensation range is: $140,000 - $325,000 USD\n   \n   - For candidates based elsewhere in the US, the compensation range is: $120,000 – $275,000 USD\n\n - Canada:\n   \n   - For candidates in Canada, the Compensation Range is : $175,000 - $385,000 CAD\n\n\n\n\nFULL-TIME EMPLOYEES AT COHERE ENJOY THESE PERKS:\n\n - A weekly lunch stipend of $75/£75 or equivalent in your local currency for lunch.\n\n - Full health and dental benefits, including a separate budget for mental health.\n\n - RRSP matching, 401K, Pension Scheme.\n\n - 100% Parental Leave top-up for up to 6 months, for either parent.\n\n - Annual enrichment benefits:\n   \n   Arts \u0026 culture, fitness/wellness, quality time, and a workspace improvement credit.\n   \n   Education \u0026 learning stipend for conferences, courses, and coaching.\n\n - 6 weeks of paid vacation (30 working days!)\n\n - Budget for traveling to other offices if you are remote, plus an annual company offsite.\n\n\n\n\nHOW AND WHERE WE WORK:\n\n - Cohere is remote-friendly, but we also have offices in Toronto, London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul with more opening soon.\n\n - For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.\n\n - For those not near an office: a co-working benefit so you can work alongside others in your city.\n\n - Everyone receives a $500 home office stipend to set up your workspace properly.\n   \n   \n\nIf any of the above doesn’t line up exactly with your exp","salary_min":175000,"salary_max":385000,"location":"Toronto, Canada","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["healthcare","payments","agents","cloud","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/cohere/be48aafc-9610-4ebd-8414-a0722a3cd59a/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T20:36:13.897Z","expires_at":"2026-09-29T13:31:52.797456Z","created_at":"2026-04-13T09:36:53.959441Z","updated_at":"2026-08-30T13:31:52.939334Z","company_name":"Cohere","company_slug":"cohere","company_logo_url":"https://www.google.com/s2/favicons?domain=cohere.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/ef4c6406-333f-41ab-8184-e9bd7afe7c50"},{"id":"2378d486-4c00-4313-98d9-dd8e3385e6f4","company_id":"a0000000-0000-0000-0000-000000000009","title":"Forward Deployed Engineer, Agentic Platform (West Coast)","slug":"applied-ai-engineer-agentic-workflows-1c208301","description":"Who are we?\n\nCohere is the leading security-first enterprise AI company.  We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.\n\nWe’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.\n\nWe obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.\n\nWe are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!\n\n\n\nABOUT NORTH:\n\nNorth https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications.\n\n\n\n\nWHY THIS ROLE?\n\nThis role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications.\n\nWe’re looking for Software Engineers with Applied AI experience who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs), from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows. You’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one.\n\nNote: between 20 - 40% travel anticipated.\n\n\n\nIN THIS ROLE, YOU WILL:\n\n - Work closely with our enterprise customers to translate high-value, ambiguous business problems into well-framed agentic workflows with clear success criteria and evaluation methodologies\n\n - Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools, APIs, and sensitive enterprise data sources, with enterprise-grade reliability and performance\n\n - Build and ship features for North, our AI workspace platform, working across the full product lifecycle from conceptualisation through production\n\n - Take ownership of scoping and shaping use cases end-to-end, flexing into whatever technical area the problem demands (including frontend) to drive the most effective solution\n\n - Contribute to shared frameworks and patterns that enable consistent, high-quality delivery across customers and teams\n\n - Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization\n\n - Travel up to 20–40% to work on-site with customers and partners\n\n\n\nYOU MAY BE A GOOD FIT IF:\n\n - You have hands-on experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code\n\n - You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute\n\n - You're deeply familiar with the LLM stack: frontier models, vector databases, and orchestration frameworks\n\n - You have a proven ability to build robust evaluation frameworks, moving well beyond trial and error, to measure agent accuracy, safety, and latency\n\n - You’re experienced working directly with customers and can lead technical discussions with enterprise stakeholders, translating ambiguous business needs into concrete technical specs\n\n - You have experience owning the full scope of a use case end-to-end\n\n - You thrive in fast-paced and ambiguous environments and can execute well even when priorities are shifting\n\n\n\nIT'S A BONUS IF YOU HAVE:\n\n - Experience setting architectural standards for AI and agentic systems across distributed teams\n\n - Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it\n\n - Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms)\n\n - Experience with enterprise security, compliance, or auditability requirements for AI systems\n\n\n\nCohere is committed to fair and transparent pay practices. The salary range listed for this role reflects the expected base compensation. Actual compensation offered will be determined by factors such as location, level, job-rela","salary_min":175000,"salary_max":385000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["rag","llm","healthcare","payments","embeddings","agents"],"apply_url":"https://jobs.ashbyhq.com/cohere/1fa01a03-9253-4f62-8f10-0fe368b38cb9/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T20:32:55.278Z","expires_at":"2026-09-29T13:31:54.221836Z","created_at":"2026-04-13T09:36:56.004203Z","updated_at":"2026-08-30T13:31:54.364691Z","company_name":"Cohere","company_slug":"cohere","company_logo_url":"https://www.google.com/s2/favicons?domain=cohere.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/2378d486-4c00-4313-98d9-dd8e3385e6f4"},{"id":"a4b7d145-78b5-46dc-a1d6-192b6a736049","company_id":"a0000000-0000-0000-0000-000000000009","title":"Forward Deployed Engineer, Agentic Platform","slug":"forward-deployed-engineer-agentic-platform-7033bcda","description":"Who are we?\n\nCohere is the leading security-first enterprise AI company.  We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems.\n\nWe’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that.\n\nWe obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft.\n\nWe are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us!\n\n\nABOUT NORTH:\n\nNorth https://cohere.com/north is Cohere's cutting-edge AI workspace platform, designed to revolutionize the way enterprises utilize AI. It offers a secure and customizable environment, allowing companies to deploy AI while maintaining control over sensitive data. North integrates seamlessly with existing workflows, providing a trusted platform that connects AI agents with workplace tools and applications.\n\n\n\nWHY THIS ROLE?\n\nThis role offers a unique opportunity to shape how enterprises harness the power of AI in real-world applications. As a bridge between our core North product and our clients’ engineering teams, you’ll be at the forefront of solving complex problems and securely integrating AI into critical sectors such as finance, healthcare, and telecommunications.\n\nWe’re looking for Software Engineers with Applied AI experience who can own the design, build, and deployment of agentic workflows powered by Large Language Models (LLMs), from early prototypes to production-grade AI agents, to deliver concrete business value in enterprise workflows. You’ll work closely with customers on real-world business problems, often building first-of-their-kind agent workflows that integrate LLMs with tools, APIs, and data sources. While our pace is startup-fast, the bar is enterprise-high: agents must be reliable, observable, safe, and auditable from day one.\n\nNote: between 20 - 40% travel anticipated.\n\n\n\nIN THIS ROLE, YOU WILL:\n\n - Work closely with our enterprise customers to translate high-value, ambiguous business problems into well-framed agentic workflows with clear success criteria and evaluation methodologies\n\n - Lead the design, build, and delivery of LLM-powered agents that reason, plan, and act across tools, APIs, and sensitive enterprise data sources, with enterprise-grade reliability and performance\n\n - Build and ship features for North, our AI workspace platform, working across the full product lifecycle from conceptualization through production\n\n - Take ownership of scoping and shaping use cases end-to-end, flexing into whatever technical area the problem demands (including frontend) to drive the most effective solution\n\n - Contribute to shared frameworks and patterns that enable consistent, high-quality delivery across customers and teams\n\n - Drive clarity in ambiguous situations, build alignment, and raise engineering quality across the organization\n\n - Travel up to 20–40% to work on-site with customers and partners\n\n\n\nYOU MAY BE A GOOD FIT IF:\n\n - You have hands-on experience building and deploying production-grade software in Python; you write clean, testable, observable, scalable code\n\n - You've built and deployed highly performant RAG and agentic applications, including agents that plan and execute multi-step tasks using patterns like ReAct or Plan-and-Execute\n\n - You're deeply familiar with the LLM stack: frontier models, vector databases, and orchestration frameworks\n\n - You have a proven ability to build robust evaluation frameworks, moving well beyond trial and error, to measure agent accuracy, safety, and latency\n\n - You’re experienced working directly with customers and can lead technical discussions with enterprise stakeholders, translating ambiguous business needs into concrete technical specs\n\n - You have experience owning the full scope of a use case end-to-end\n\n - You thrive in fast-paced and ambiguous environments and can execute well even when priorities are shifting\n\n\n\nIT'S A BONUS IF YOU HAVE:\n\n - Experience setting architectural standards for AI and agentic systems across distributed teams\n\n - Experience flexing into unfamiliar technical areas, such as frontend, when the problem calls for it\n\n - Exposure to regulated or sensitive industry environments (finance, healthcare, telecoms)\n\n - Experience with enterprise security, compliance, or auditability requirements for AI systems\n\n\n\nCohere is committed to fair and transparent pay practices. The salary range listed for this role reflects the expected base compensation. Actual compensation offered will be determined by factors such as location, level, job-relate","salary_min":175000,"salary_max":385000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["llm","payments","rag","agents","healthcare","embeddings"],"apply_url":"https://jobs.ashbyhq.com/cohere/b0bcef37-1d20-414f-aade-c54942d63df9/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T20:30:58.199Z","expires_at":"2026-09-29T13:31:53.365783Z","created_at":"2026-04-13T09:36:54.973831Z","updated_at":"2026-08-30T13:31:53.50782Z","company_name":"Cohere","company_slug":"cohere","company_logo_url":"https://www.google.com/s2/favicons?domain=cohere.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a4b7d145-78b5-46dc-a1d6-192b6a736049"},{"id":"8f5683c8-4601-44f3-ae28-99878029e10f","company_id":"a0000000-0000-0000-0000-000000000001","title":"Head of Policy Design, Societal Harms","slug":"head-of-policy-design-societal-harms-25b5c82a","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the role \n Anthropic's Safeguards organization builds the policies, evaluations, and detection and enforcement systems that define and hold the limits on how Claude can be used. In this role, you'll lead our policy design team, managing the teams responsible for radicalization, child safety, user well-being, harmful manipulation, and election integrity, among other harm areas.\n The team is responsible for understanding and defining the risks that come with engaging with Claude, how those risks materialize in the real world, and the mitigations needed to prevent them. As the manager, you'll work with your team to draw the boundaries between what is and is not allowed, then partner with research, product, and engineering to build the right interventions. Mitigating these harms takes the whole stack: the values and judgment trained into the model itself, the policies and detection systems we enforce on top of it, and the interventions we build into our products. More capable models, new product surfaces, and new user behaviors will keep testing these boundaries, so the team's policies have to keep pace.\n You'll work closely with product to develop and iterate on the strategy and vision for how our safety layers fit together, and with your team and cross-functional partners to decide which mitigations make the most sense and how to implement them. You'll also coordinate policy decisions across the portfolio: ensuring they're made with the right stakeholders in the room, tracked over time, and applied consistently across harm areas and product surfaces.\n This is a leadership role for someone who combines expertise in the harm areas themselves with fluency in how frontier models are actually developed and deployed, and who does their best work across team boundaries. You'll spend as much time developing the leads who own each harm area as you will on the policy questions themselves.\n *Important context for this role: some of the work involves exposure to explicit content, including material of a sexual, violent, or psychologically disturbing nature.\n Key responsibilities \n \n \n Lead, develop, and grow the managers and teams responsible for the consumer harms portfolio, including child safety, user well-being, harmful manipulation, and election integrity\n \n Coordinate policy decisions across the portfolio, and build the mechanisms that keep them tracked, consistent, and legible — so stakeholders know what was decided, why, and who owns what\n \n Set the strategy for how mitigations built on top of the model — policies, detection and enforcement systems, and product interventions — complement what is trained into the model itself, partnering closely with the alignment training team that owns Claude's character\n \n Prioritize across harm areas competing for the same resources, and make those tradeoffs and their rationale clear to leadership\n \n Serve as the escalation point for high-severity and ambiguous consumer harms decisions, including rapid response to emerging risks\n \n Partner with engineering, data science, product, legal, and research across the model development cycle so consumer harms considerations are represented from training through launch, on every surface where Claude is deployed\n \n Engage external experts, civil society organizations, and regulators, and translate that engagement into stronger policy and enforcement\n \n Minimum qualifications \n \n \n Experience leading teams — including managing managers or senior specialists — in AI safety, product policy, or a related field\n \n Deep, applied familiarity with consumer harm areas such as child safety, mental health and well-being, manipulation, or election integrity, and good judgment about how these harms differ in mechanism, severity, and mitigation\n \n A track record of exceptional cross-team collaboration: building durable working relationships with teams you don't control, and getting to shared decisions where ownership is genuinely distributed\n \n Working understanding of how frontier models are developed and deployed — the training and fine-tuning cycle, evaluations, and launch processes — and how different model environments (consumer products, APIs, agentic tools) change both risk and the mitigations available\n \n Experience translating policy positions into mechanisms that can be enforced and measured, and communicating the reasoning to technical and non-technical audiences, including executives\n \n Sound judgment in ambiguous, high-consequence decisions, and comfort making a call and escalating appropriately on incomplete information\n \n Preferred qualifications \n \n \n Subject-matter depth in one","salary_min":330000,"salary_max":395000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["generative-ai","agents","llm","alignment","fine-tuning","healthcare","rust"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5407418008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T19:56:10Z","expires_at":"2026-09-29T13:30:21.361128Z","created_at":"2026-08-29T13:30:22.347939Z","updated_at":"2026-08-30T13:30:21.508142Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/8f5683c8-4601-44f3-ae28-99878029e10f"},{"id":"a9304478-6b78-4ca2-a86c-1622c0c977f2","company_id":"654d4532-88db-435d-8a6f-161b8c5a491e","title":"Senior Manager, Data Science - Styling Algorithms","slug":"senior-manager-data-science-styling-algorithms-ed2bd7cb","description":"About Stitch Fix, Inc. \n Stitch Fix (NASDAQ: SFIX) Stitch Fix is redefining retail by combining human creativity with advanced data science and Generative AI. As we build the future of personalized shopping, we’re equally committed to building yours.  We believe in investing in our team as much as our technology. Join us to be a trendsetter in the industry and help us redefine what’s possible for our clients, while we help you reach your full potential.\n About the Role \n At Stitch Fix, we are at the forefront of innovation, creating cutting-edge solutions that blend fashion, technology, and data science. Our data science team combines machine learning with expert human judgment to generate innovative recommendations and insights that transform the way our clients discover what they love. We believe in a curiosity-driven data science culture where members are empowered to deliver impact through end-to-end model development. The diversity of the problems that we work on and the data-rich environment of our business make it possible, even essential, to bring the tools of multiple disciplines to bear on our hardest problems.  \n We are looking for an experienced Styling Algorithms Team Manager to lead a group of talented machine learning engineers and data scientists. In this role, you will shape the future of fashion technology by driving the development and deployment of our styling algorithms, which empower our human stylists to delight clients by nailing their fit and style. This includes ML-, AI-, and product-driven feature curation and testing for our proprietary styling platform, as well as client-facing AI personalization experiences, such as Stitch Fix Vision, our virtual try-on.\n Responsibilities: \n \n Champion bold AI and ML interventions to improve our styling experiences, enabling our stylists to have a multiplicative impact on their client connection points.\n Likewise, actively shape the product roadmap for direct client-facing styling experiences, expanding the breadth and depth of personalization touchpoints to complement and inform our human stylists.\n Inspire your team by fostering a culture of ideation, ownership, feedback, and collaboration between team members and with cross-functional partners.\n Act as an advocate for our Styling and Merchandising teams, empowering partners to understand trends in stylist feedback and inventory surfacing algorithms for rapid action on emergent opportunities. \n Work with product managers, other data science teams, UI/UX designers, and business leaders to define and optimize against business objectives for our suite of styling experiences.\n Oversee the end-to-end algorithm development lifecycle, from ideation and experimentation to testing and deployment in a production environment.\n Identify and implement best practices for team collaboration, code quality, use of AI, and data management.\n Stay up-to-date with advancements in AI-assisted development, AI-enabled product experiences, machine learning, and fashion technology.\n \n About You \n This is what you’ll need to succeed in this role from day 1. \n Requirements: \n \n Bachelor’s Degree in a quantitative field such as Computer Science, Statistics, Physics, Mathematics, or a related field required. Master’s or PhD preferred. \n 5+ years of experience in design and deployment of AI and ML solutions, ideally in retail personalization, with an emphasis on agentic capabilities.\n 2+ years of experience as a team technical lead or direct people manager.\n Ability to write and review production-grade code, ideally in Python.\n Applied knowledge of AI-assisted coding best practices and development of agentic product solutions.\n Excels at building trust with your team, stakeholders, and technical partners.\n Excellent communication skills with the ability to articulate complex technical concepts to business audiences.\n Experience with online A/B testing, experimentation frameworks, and performance metrics.\n Familiar with cloud-based infrastructure and distributed data systems.\n Compensation and Benefits This role will receive a competitive salary, benefits, and equity. The salary for US-based employees hired into this role will be aligned with the range below, which includes our three geographic areas. A variety of factors are considered when determining someone’s compensation–including a candidate’s professional background, experience, location, and performance. This position is eligible for an annual bonus, and new hire and ongoing grants of restricted stock units, depending on employee and company performance. In addition, the position is eligible for medical, dental, vision, and other benefits. Applicants should apply via our internal or external careers site. \n Salary Range\n $200,000 — $246,000 USD \n This link leads to the machine readable files that are made available in response to the federal Transparency in Coverage Rule and includes negotiated service rates and out-of-network allowed amounts","salary_min":200000,"salary_max":246000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["generative-ai","payments","healthcare","agents","data-science"],"apply_url":"https://www.stitchfix.com/careers/jobs?gh_jid=8164607\u0026gh_jid=8164607","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-28T16:49:32Z","expires_at":"2026-09-29T13:49:16.042671Z","created_at":"2026-08-29T13:50:46.465007Z","updated_at":"2026-08-30T13:49:16.172549Z","company_name":"Stitch Fix","company_slug":"stitch-fix","company_logo_url":"https://www.google.com/s2/favicons?domain=stitchfix.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a9304478-6b78-4ca2-a86c-1622c0c977f2"},{"id":"0da6da6c-77b3-4ba4-97ca-4eb47129b83d","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Senior Data Scientist, Ads Integrity","slug":"senior-data-scientist-ads-integrity-254eca52","description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n Reddit is continuing to grow our teams with the best talent. This role is completely remote friendly within the United States. If you happen to live close to one of our physical office locations (San Francisco, Los Angeles, New York City \u0026 Chicago) our doors are open for you to come into the office as often as you'd like.\n Reddit is poised to innovate and grow like never before, and Safety is a critical accelerant of that growth. The Safety org is Reddit’s central Trust \u0026 Safety organization, protecting users from bad experiences by stopping harmful content, behaviors, and abuse across the platform. We are looking for a Senior Data Scientist to lead ads fraud detection and scaled enforcement within Safety. You will partner closely with Ads Product, Engineering, Machine Learning, Operations, Policy, Legal, and fellow Safety data scientists to identify emerging ads fraud, define rigorous measurement and evaluation standards, and turn investigations into durable signals, models, rules, and enforcement pipelines. This is a high-impact role with exceptional opportunity for ownership and growth: as an early leader in a greenfield space, you will help define the strategy, shape cross-functional roadmaps, build foundational capabilities, and expand your scope as Reddit’s ads integrity program matures.\n Responsibilities\n \n Lead the measurement and detection strategy for ads fraud by defining fraud taxonomies, labels, sampling plans, metrics, and evaluation frameworks that make performance measurable and defensible.\n Analyze large, complex datasets and networks of behavior to uncover emerging fraud patterns, size their impact, identify root causes, and translate findings into detection and enforcement requirements.\n Design and develop scalable ads fraud detection and enforcement pipelines in partnership with Engineering and Machine Learning, including feature generation, rules and models, near-real-time scoring, actioning, review feedback loops, and observability.\n Own the full detection lifecycle: backtesting, threshold calibration, offline and online evaluation, launch validation, experimentation, monitoring, drift detection, incident response, rollback, and retirement.\n Build and maintain statistical, machine learning, and GenAI-enabled models or prototypes that improve fraud detection, risk identification, investigator efficiency, and enforcement quality.\n Balance fraud loss, platform and advertiser risk, customer experience, false-positive costs, operational capacity, and business goals when recommending detection thresholds and enforcement strategies.\n Partner across Ads and Safety to shape strategy and roadmaps, strengthen data foundations, close policy and enforcement gaps, and ensure solutions meet governance and compliance standards.\n Translate complex analyses into clear narratives and actionable recommendations for technical and non-technical stakeholders, including senior leaders, and mentor other data scientists and analysts.\n \n Qualifications\n \n Relevant experience in Data Science, Applied Science, or a related quantitative role, preferably in ads fraud, financial fraud, or account risk, Trust \u0026 Safety, platform integrity, or enforcement engineering.\n Ph.D. or M.S. degree in Statistics, Economics, Computer Science, Applied Mathematics, or another quantitative field; with an M.S., 4+ years of industry data science experience, or with a Ph.D., 2+ years of industry data science experience.\n Demonstrated experience building or materially shaping production detection and automated enforcement pipelines, including batch or streaming data, feature engineering, rules or models, decisioning, monitoring, and feedback loops.\n Strong command of fraud or abuse detection methods and evaluation, including label design, precision and recall tradeoffs, calibration, threshold selection, false-positive analysis, drift detection, and adversarial adaptation.\n Experience partnering closely with Product and Engineering teams to translate analyses and prototypes into reliable production systems; experience working across Ads, Safety, fraud, risk, or platform-integrity organizations is preferred.\n Experience applying AI and large language models (LLMs) to practical data science workflows, such as threat discovery, content classification, signal development, investigation automation, or detection and enforcement systems.\n Deep understanding of complex behavioral networks or large-scale activity patterns; experience with methods such as graph or network analysis, clustering","salary_min":190800,"salary_max":267100,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["generative-ai","nlp","healthcare","llm","data-science"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/8157580","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T20:49:14Z","expires_at":"2026-09-29T13:38:57.712667Z","created_at":"2026-08-29T13:39:34.881738Z","updated_at":"2026-08-30T13:38:57.847667Z","company_name":"Reddit","company_slug":"reddit","company_logo_url":"https://www.google.com/s2/favicons?domain=www.reddit.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0da6da6c-77b3-4ba4-97ca-4eb47129b83d"},{"id":"130278d1-56fd-43d0-bd53-bc36938ae400","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Staff Fullstack Engineer, AI Acceleration Team","slug":"staff-fullstack-engineer-ai-acceleration-team-bbf7616e","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n Staff FullStack Engineer, AI Acceleration Team\n The AI Acceleration Team\n The AI Acceleration Team builds AI features right where identity and agents meet. Companies are handing real access to AI agents faster than their controls can keep up, and two problems show up first: how do you authorize what an agent is allowed to do on someone's behalf, and how do you keep both people and agents from being phished? We take those on directly.\n Our North Star: to get AI right, you have to get identity right. We are a new team, and we shape the problems as much as we solve them. We bring a product mindset to the work: we dig into what customers actually need, define the outcome, and build toward it. We move fast, stay close to the real problem, and are honest about what works.\n The Staff FullStack Engineer Opportunity\n As a Staff FullStack Engineer on the AI Acceleration Team, you will own the technical build for solving agent authorization and phishing resistance. You see what needs doing and start it. This is 0-to-1 work, meaning you will move on problems before they are fully specified, always keeping customer success as the ultimate bar.\n You will help shape which problems we take on, make architectural calls that outlive any single project, and set the technical bar for how we work. You will enforce least privilege for what agents can do and make phishing-resistant access the default. We build with Vercel and AWS, and you will likely work heavily in JavaScript/TypeScript and Java.\n What you'll be doing\n \n Solve core authorization challenges: Define how companies authorize agent actions and enforce least privilege for what an agent can do on a user's behalf.\n Design secure access: Build phishing-resistant authentication and authorization for both people and the agents acting for them.\n Shape the product: Bring a product mindset to dig into what customers need, define the desired outcomes, and build toward them rather than just executing solutions.\n Own the quality bar: Act as the voice for product and quality judgment in the room, taking ownership of the outcome, not just the code.\n Drive technical architecture: Make and defend architectural decisions on distributed systems and complex API integrations that will scale as the work grows.\n Modernize development: Advance how we use AI across our development lifecycle—how we design, review, and ship—and bring the rest of the team along with you.\n Coach and multiply: Raise the technical bar of the entire team, building judgment in others rather than trying to solve everything yourself.\n Improve engineering excellence: Spot and prioritize tech debt, driving improvements beyond feature work (CI/CD, observability, documentation, reliability, and support).\n Stay customer-aware: Build with a clear, direct line to the customer problem and the outcome you're solving for, even if you aren't in every customer conversation.\n \n What you'll bring to the role\n \n A self-starter mentality: The ability to spot what matters, drive work autonomously, and thrive in ambiguity while helping to form a new charter.\n Advanced AI tool proficiency: The ability to apply AI meaningfully across the software development lifecycle, evaluate new tooling with good judgment, and establish practices for the wider team.\n Architectural expertise: Proven experience defining scalable backend architectures and integrating complex APIs with modern web technologies, including making decisions with lasting, org-wide impact.\n Security fundamentals: A solid grasp of web authentication and authorization, including how auth flows work and how to secure sensitive user data.\n Backend proficiency: Deep expertise in building reliable, secure, enterprise-grade software in Java or another type-safe language.\n Frontend flexibility: High proficiency in JavaScript/TypeScript with true fullstack range, including the ability to ship robust frontends.\n Cloud infrastructure knowledge: Strong cloud architecture fundamentals, with experience designing and operating large-scale services on AWS.\n \n Extra credit\n \n Background working on a zero-to-one, startup-like team.\n Track record of leading a team through a real shift in how they work (e.g., AI adoption, new developer tooling, or cultural shifts).\n Familiarity with developing Identity and Access Management (IAM) tooling.\n \n P25592\n Below is the annual salary range for candidates located in Canada. Your actual salary will depend on factors such as your skills, quali","salary_min":160000,"salary_max":220000,"location":"Toronto, Canada","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["healthcare","distributed-systems","cloud","agents","fullstack"],"apply_url":"https://www.okta.com/company/careers/opportunity/8109399?gh_jid=8109399","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T20:41:56Z","expires_at":"2026-09-29T13:39:37.302166Z","created_at":"2026-08-29T13:40:17.273768Z","updated_at":"2026-08-30T13:39:37.440039Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/130278d1-56fd-43d0-bd53-bc36938ae400"},{"id":"280219b5-1d1a-4b23-8422-baab1f0239cd","company_id":"63bced38-3605-4e57-99f3-e213b2d40bf3","title":"Sr. Manager, Engineering","slug":"sr-manager-engineering-13c89eb3","description":"Opportunity Overview:  \n We are seeking a Senior Engineering Manager to lead our Review Engineering team — roughly 20+ engineers across three squads in the US and India — building the workflows and capabilities that let clinical operations staff deliver care at scale, efficiently and with high quality. Leading through dedicated technical leads on each squad, you'll own the reliability and technical direction of Review's systems while partnering closely with Product, Design, Security, Clinical Operations, and peer engineering teams on shared platforms. This is an opportunity to shape a growing, business-critical part of Cohere's platform and to grow the next generation of engineering leaders in health technology.\n This is a remote-first role that may require travel to Boston, MA for new hire onboarding and occasional in-person team meetings and company events.\n What you’ll do: \n \n Lead 20+ engineers across multiple agile squads (US and India) through dedicated technical leads\n Own production reliability for Review-owned systems — incident response, root-cause RCAs, and cross-functional tiger teams for major incidents\n Set technical vision and provide leadership across design and sprint processes, partnering with Staff Engineers\n Drive delivery transparency through sprint metrics, catching risk early and informing data-driven interventions\n Partner with Product, Design, Security, Clinical Ops, and peer engineering teams (including our Hyderabad group) on shared systems and initiatives\n Own hiring, leveling, and career growth for direct reports and their leads; help attract and retain top talent\n Build a culture that grows early-career engineers into future health-tech leaders, with a bias toward team autonomy\n Champion testing, quality, and security practices in a regulated (HIPAA/SOC2) environment\n \n What you’ll need: \n \n 5+ years managing software engineering teams in a fast-paced, agile environment, including 3+ years leading multiple teams through technical leads or managers\n Experience leading distributed/multi-site teams across time zones (e.g. US/India), including partnering with groups outside your direct reporting line\n Hands-on full-stack engineering background\n Proven ability to own production systems and incident response, ideally in a regulated (healthcare, HIPAA/SOC2) environment\n Strong grounding in modern development practices (version control, unit testing, CI/CD)\n Experience designing and scaling distributed/microservices systems for high-throughput, high-growth products\n A passion for quality products and high-performing, autonomous teams\n Bachelor's degree in computer science, software engineering, or equivalent experience\n \n Pay \u0026 Perks: \n 💻 Fully remote opportunity with about 5% travel\n 🩺 Medical, dental, vision, life, disability insurance, and Employee Assistance Program \n 📈 401K retirement plan with company match; flexible spending and health savings account \n 🏝️ Flex Time Off + company holidays\n 👶 Up to 14 weeks of paid parental leave \n 🐶 Pet insurance  \n The salary range for this position is $185,000 to $225,000 annually; as part of a total benefits package which includes health insurance, 401k and bonus. In accordance with state applicable laws, Cohere is required to provide a reasonable estimate of the compensation range for this role. Individual pay decisions are ultimately based on a number of factors, including but not limited to qualifications for the role, experience level, skillset, and internal alignment. \n Interview Process*: \n \n Connect with Talent Acquisition for a Preliminary Phone Screening\n Meet your Hiring Manager!\n Live System Design Exercise \n Project Discussion \n Cross Functional Interview \n \n *Subject to change\n About Cohere Health: \n Cohere Health’s clinical intelligence platform and agentic AI-powered solutions connect health plans’ strategic goals and providers’ needs, optimizing the speed, cost, and quality of care. With an enterprise approach that streamlines payer-provider decision-making across the care continuum–including policy, prior authorization, payment accuracy, and more–the company improves collaboration and reduces burden, resulting in up to 8x ROI and 94% provider satisfaction. \n With the acquisition of ZignaAI, we’ve further enhanced our platform by launching our Payment Integrity Suite, anchored by Cohere Validate™, an AI-driven clinical and coding validation solution that operates in near real-time. By unifying pre-service authorization data with post-service claims validation, we’re creating a transparent healthcare ecosystem that reduces waste, improves payer-provider collaboration and patient outcomes, and ensures providers are paid promptly and accurately.\n Cohere Health’s innovations continue to receive industry wide recognition. We’ve been named to the 2025 Inc. 5000 list and in the Gartner® Hype Cycle™ for U.S. Healthcare Payers (2022-2025), and ranked as a Top 5 LinkedIn","salary_min":185000,"salary_max":225000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["payments","agents","microservices","healthcare"],"apply_url":"https://job-boards.greenhouse.io/coherehealth/jobs/7979401003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T18:00:50Z","expires_at":"2026-09-29T13:36:35.153666Z","created_at":"2026-08-29T13:36:57.646684Z","updated_at":"2026-08-30T13:36:35.288736Z","company_name":"Cohere Health","company_slug":"cohere-health","company_logo_url":"https://www.google.com/s2/favicons?domain=coherehealth.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/280219b5-1d1a-4b23-8422-baab1f0239cd"},{"id":"e9df7d6e-9243-4269-8196-cc7374752000","company_id":"63bced38-3605-4e57-99f3-e213b2d40bf3","title":"Sr. Software Engineer, Data Platform","slug":"sr-software-engineer-data-platform-56629500","description":"Opportunity Overview:  \n This is a remote-first role that may require travel to Boston, MA for new hire onboarding and occasional in-person team meetings and company events.\n We’re seeking a Senior Software Engineer to join our Data Platform team and take ownership of designing and delivering large-scale, reliable, and governed data pipelines that power analytics, operations, and clinical intelligence across Cohere Health. This role is ideal for an engineer who thrives on solving complex data challenges, mentoring others, and raising engineering standards while contributing to scalable and sustainable platform growth.\n As a Senior Software Engineer of the data platform team, you’ll operate across the end-to-end data lifecycle—from ingestion to transformation to integration—driving solutions that align with architectural best practices, governance needs, and business outcomes. You’ll partner closely with analytics engineers, architects, and product stakeholders to ensure that data products are performant, compliant, and trustworthy.\n What you’ll do: \n \n Lead the design and implementation of complex data pipelines and infrastructure across multiple domains\n Mentor junior engineers, sharing expertise and raising team-wide engineering standards\n Implement and enforce data quality, schema validation, and observability practices to ensure trustworthy outputs\n Contribute to architecture discussions and tool evaluation, helping to shape platform scalability and governance alignment\n Write clean, maintainable, and testable code in Python and SQL, following best practices in version control, CI/CD, and documentation\n Optimize and monitor production workflows using tools such as Airflow, dbt, Athena, EMR, Kafka, and Iceberg/Parquet\n Collaborate with cross-functional stakeholders (analytics, product, compliance) to ensure technical solutions meet business needs\n Participate in on-call rotations to support critical platform jobs and reduce operational disruptions\n Champion a culture of excellence, accountability, and continuous improvement through code reviews, documentation, and knowledge sharing\n \n What you’ll need: \n \n Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field is required\n 5+ years of experience in data engineering or software development with a strong focus on data infrastructure\n Demonstrated success designing and delivering large-scale, reliable, and governed data infrastructure projects\n Track record of building and maintaining production grade systems using APIs\n Strong proficiency in Python and SQL, with experience applying software engineering rigor to data workflows (testing, version control, observability)\n Hands-on experience with modern data tools such as Airflow, dbt, AWS (EMR, Athena, S3), Iceberg, Parquet, and Kafka\n Track record of mentoring engineers and raising team-wide engineering standards through code reviews, documentation, and knowledge sharing\n Ability to work effectively in a fast-paced, agile environment, collaborating across technical and non-technical stakeholders\n Experience with healthcare data (claims, eligibility, clinical, EHR) is strongly preferred\n Understanding of data security, privacy, and compliance practices (HIPAA or similar) in pipeline and platform design\n Experience with snowflake, Databricks is a plus\n Bachelor’s or Master’s degree in Computer Science, Data Engineering, or a related field is a plus\n \n  \n Pay \u0026 Perks: \n 💻 Fully remote opportunity with about 5% travel\n 🩺 Medical, dental, vision, life, disability insurance, and Employee Assistance Program \n 📈 401K retirement plan with company match; flexible spending and health savings account \n 🏝️ Flex Time Off + company holidays\n 👶 Up to 14 weeks of paid parental leave \n 🐶 Pet insurance  \n The salary range for this position is $130,000 to $160,000 annually; as part of a total benefits package which includes health insurance, 401k and bonus. In accordance with state applicable laws, Cohere is required to provide a reasonable estimate of the compensation range for this role. Individual pay decisions are ultimately based on a number of factors, including but not limited to qualifications for the role, experience level, skillset, and internal alignment. \n  \n Interview Process*: \n \n Connect with Talent Acquisition for a Preliminary Phone Screening\n Meet your Hiring Manager!\n Feature Design\n System Design\n Behavioral Interview\n \n *Subject to change\n  \n About Cohere Health: \n Cohere Health’s clinical intelligence platform and agentic AI-powered solutions connect health plans’ strategic goals and providers’ needs, optimizing the speed, cost, and quality of care. With an enterprise approach that streamlines payer-provider decision-making across the care continuum–including policy, prior authorization, payment accuracy, and more–the company improves collaboration and reduces burden, resulting in up to 8x ROI and 94% provider s","salary_min":130000,"salary_max":160000,"location":"United States","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["healthcare","data-pipeline","cloud","payments","agents"],"apply_url":"https://job-boards.greenhouse.io/coherehealth/jobs/7978386003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T16:37:59Z","expires_at":"2026-09-29T13:36:35.433402Z","created_at":"2026-08-27T13:36:40.138107Z","updated_at":"2026-08-30T13:36:35.567586Z","company_name":"Cohere Health","company_slug":"cohere-health","company_logo_url":"https://www.google.com/s2/favicons?domain=coherehealth.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e9df7d6e-9243-4269-8196-cc7374752000"},{"id":"44046e1e-69ad-4692-9110-7bb87edaadaf","company_id":"43dd17db-bec3-4ebb-a432-f71d57a9aa47","title":"Staff Software Engineer, Imaging","slug":"staff-software-engineer-imaging-4ba96095","description":"THE OPPORTUNITY\n\ninsitro is a physical AI company dedicated to unlocking causal human biology and accelerating the delivery of better medicines to patients. Our unique Virtual Human™ platform identifies novel, high-impact genetic intervention points, which our TherML™ platform translates into therapeutics—whether small molecules, biologics, or oligos. With multiple programs in metabolic disease and neuroscience advancing toward the clinic, and our first IND submission slated for the second half of this year, we are at a pivotal inflection point.\n\nAs a Staff Software Engineer on our Imaging Software team, you will define and expand our computer vision and ML infrastructure across the full imaging data lifecycle — from on-microscope acquisition to high-throughput ML pipelines. You'll build the platform features that make novel imaging modalities and ML-derived phenotypes integral to our discovery workflows, partnering daily with lab scientists, ML scientists, and our microscopy team to turn research prototypes into validated screening workflows that run reliably at laboratory automation scale. This is a chance to set the technical direction for how imaging, automation, and machine learning converge in drug discovery.\n\nBased in South San Francisco, this position reports directly to the Director of Imaging, Cellular Machine Learning and offers an in-person hybrid schedule of three days per week.\n\n\n\n\nRESPONSIBILITIES\n\nPlatform \u0026 Tooling\n\n• Platform Enablement: Partner with lab and ML scientists to design, develop, and scale the platform capabilities needed to run and interpret ML-powered high-content imaging screens\n\n• User Tooling: Build and evolve robust tools and interactive interfaces for data exploration, quality assessment, and visualization so scientists can iterate quickly on experimental data\n\n• Architectural Ownership: Own complex, end-to-end projects, making thoughtful architectural trade-offs, and delivering incrementally with long-term maintainability in mind\n\nProduction Hardening \u0026 Data Integrity\n\n• Production Hardening: Scale and harden complex image processing and ML workflows, taking them from research prototypes to systems that reliably process millions of images per day\n\n• Data Integrity: Set and uphold best-in-class practices for data integrity, lineage tracking, reproducibility, and observability across the entire imaging data lifecycle\n\n• Documentation: Write clear, exemplary technical specifications and documentation that others build on\n\nCross-Functional Partnership\n\n• Scientific Translation: Work closely with lab scientists, ML scientists, and microscopy teams to translate complex experimental needs into clear, actionable technical plans and shipped software\n\n• Mentorship: Raise the technical bar across the team by sharing knowledge and mentoring other engineers\n\n \n\n\nABOUT YOU\n\nExperience \u0026 Qualifications\n\n• Proven Tenure: 8+ years of professional experience building and operating production-grade software and high-throughput data pipelines, primarily in Python\n\n• ML Platform Depth: You have designed, built, and deployed scientific computing pipelines, visualizations, and QC processes for large-scale imaging or similarly high-dimensional datasets\n\n• Distributed Systems Stack: Hands-on experience with a Python-first ML stack, distributed compute (e.g., PyTorch/Lightning, Ray, Kubernetes), and workflow orchestration (e.g., Argo, Airflow, or redun)\n\n• End-to-End Delivery: A track record of owning complex systems from architecture through production operation\n\nCore Competencies\n\n• Cross-Functional Partnership: You thrive alongside scientists and excel at translating abstract research needs into practical, scalable software\n\n• Mission-Driven: You're motivated by enabling scientific breakthroughs through robust platform engineering\n\n• Force Multiplier: You enjoy mentoring and leveling up the engineers around you \n\n\n\n\nCOMPENSATION \u0026 BENEFITS AT INSITRO\n\nOur target starting salary for successful US-based applicants for this role is $219,000 - $233,000. To determine starting pay, we consider multiple job-related factors including a candidate's skills, education and experience, market demand, business needs, and internal parity. We may also adjust this range in the future based on market data.\n\nThis role is eligible for participation in our Annual Performance Bonus Plan (based on company targets by role level and annual company performance) and our Equity Incentive Plan, subject to the terms of those plans and associated policies.\n\n\n\nIn addition, insitro also provides our employees:\n\n - 401(k) plan with employer matching for contributions\n\n - Excellent medical, dental, and vision coverage as well as mental health and well-being support\n\n - Open, flexible vacation policy\n\n - Paid parental leave of at least 16 weeks to support parents who give birth, and 10 weeks for a new parent (inclusive of birth, adoption, fostering, etc)\n\n - Quarterly budget for books and","salary_min":219000,"salary_max":233000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["healthcare","payments","data-pipeline","fine-tuning","pytorch","computer-vision","distributed-systems"],"apply_url":"https://jobs.ashbyhq.com/insitro/ff6605ae-4961-4a06-b656-6d7dc665d990/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T22:43:18.642Z","expires_at":"2026-09-29T13:36:50.099247Z","created_at":"2026-08-26T13:36:56.743297Z","updated_at":"2026-08-30T13:36:50.234419Z","company_name":"Insitro","company_slug":"insitro","company_logo_url":"https://www.google.com/s2/favicons?domain=insitro.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/44046e1e-69ad-4692-9110-7bb87edaadaf"},{"id":"c176fb2a-4dab-4c84-9b30-9565eee362ea","company_id":"46e2df02-755e-46ce-a584-3f5881f34183","title":"Product Manager, Finance","slug":"product-manager-finance-c4294318","description":"About Turing \n Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com .  \n  \n Position Overview \n We are looking for an experienced Product Manager to lead the strategy, roadmap, and execution for platforms supporting Back Office Operations, especially around Fund controller accounting and Global Business Finance. The ideal candidate brings strong product management experience combined with deep knowledge of financial operations, operational controls, and controller functions.\n This role will partner closely with business stakeholders, engineering, and operations teams to modernize back-office platforms and improve operational efficiency. While familiarity with AI is a plus, the primary focus is on delivering business value through well-designed operational systems rather than building AI solutions.\n Key Responsibilities \n \n Own the product vision, roadmap, and prioritization for Operations \u0026 Controls platforms.\n Lead product discovery by understanding business problems, operational workflows, and stakeholder requirements.\n Partner with Back Office Operations, Controllers, Finance, and Technology teams to improve operational processes.\n Drive modernization initiatives in fund control accounting workflow automation, and operational reporting.\n Build and manage the product backlog, define user stories, and prioritize features based on business value.\n Coordinate delivery across engineering, architecture, and business stakeholders.\n Track milestones, dependencies, risks, and delivery progress.\n Promote transparency and effective stakeholder communication throughout the product lifecycle.\n Identify practical opportunities where AI and automation tools can improve productivity, decision-making, and operational efficiency.\n Ensure solutions meet governance, audit, and operational control requirements.\n \n Required Qualifications \n \n 5+ years of experience as a Product Owner, Product Manager, or Senior Business Analyst within Financial Services.\n Strong experience supporting Back Office Operations, Fund Controllers, and Finance Operations .\n Has fund accounting domain literacy , hands-on exposure to at least one fund accounting/admin platform, exception management\n Experience building or enhancing corporate back-office platforms and operational systems .\n Demonstrated experience translating fund control requirements — NAV integrity, cash/position break resolution, and controller sign-off workflows — into product specs and acceptance criteria that satisfy audit and governance standards.\n Excellent stakeholder management and cross-functional collaboration skills.\n Proven ability to manage product roadmaps, planning, prioritization, and execution.\n Strong analytical, communication, and problem-solving skills.\n Familiarity with AI tools (e.g., ChatGPT, Copilot, Gemini) and understanding of where AI can improve operational workflows. Hands-on AI solution development is not required. \n Ability to work effectively with engineering teams and understand modern software delivery practices.\n \n Preferred Qualifications \n \n Experience with platforms such as Geneva/SS\u0026C, Eagle, Advent, Paxus , or similar fund accounting and operations systems.\n Experience working with fund administrators or investment operations teams.\n Experience with Agile product delivery.\n Exposure to workflow automation, cloud platforms, or modern enterprise applications.\n \n Compensation Range:  $175,000 - $215,000 total cash   #LI-VC1 \n Values \n \n We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value. \n We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection \n We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.\n \n Advantages of joining Turing \n \n Work at the frontier of AI , helping the world’s leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks. \n Contribute to leading-edge AI research and showcase your work at ","salary_min":175000,"salary_max":215000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["code-generation","reinforcement-learning","healthcare","agents"],"apply_url":"https://job-boards.greenhouse.io/turing/jobs/6150811004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T20:29:31Z","expires_at":"2026-09-29T13:35:13.232941Z","created_at":"2026-08-26T13:35:15.599435Z","updated_at":"2026-08-30T13:35:13.370674Z","company_name":"Turing","company_slug":"turing","company_logo_url":"https://www.google.com/s2/favicons?domain=turing.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c176fb2a-4dab-4c84-9b30-9565eee362ea"},{"id":"a85f6a22-2c3d-4d63-bc92-fb6bab844254","company_id":"72014eb6-e84d-48c2-af5c-5424ebec0b3c","title":"Senior Staff Machine Learning Systems Engineer, Ads ML Platform","slug":"senior-staff-machine-learning-systems-engineer-ads-ml-platform-555ec238","description":"Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit www.redditinc.com .\n Reddit has a flexible workforce! If you happen to live close to one of our physical office locations our doors are open for you to come into the office as often as you'd like. Don't live near one of our offices? No worries: You can apply to work remotely in any country in which we have a physical presence\n About Reddit Reddit is a community of communities, built on shared interests, passion, and trust. With 100,000+ active communities and 101M+ daily active unique visitors, we’re one of the largest sources of conversation and knowledge on the internet. For more information, visit redditinc.com .\n Team Overview \n The Ads ML Platform team builds infrastructure that accelerates high-scale ML systems and tooling for Ads ML, while extending reusable capabilities to broader Reddit ML use cases where appropriate. Our systems help ML engineers move faster across the full development lifecycle: creating features, generating training data, running offline experiments, validating model quality, launching production models, and operating ML systems reliably.\n We are looking for a Senior Staff Machine Learning Systems Engineer to lead the technical strategy for the end-to-end Ads ML engineer lifecycle. The initial focus will be on the feature development and training iteration loop: making it faster and easier for ML engineers to build features, generate reliable training data, run experiments, and move from idea to validated model improvement. Over time, this scope will expand into serving and online experimentation workflows, creating a more seamless path from offline iteration to production impact.\n This is a senior technical leadership role for someone who can combine deep systems expertise, production ML experience, architectural judgment, and cross-team influence.\n What You’ll Do \n \n Own the technical strategy for the end-to-end Ads ML engineer lifecycle, starting with feature development, training data, offline experimentation, and model iteration workflows.\n Align Ads ML platform priorities with Reddit’s broader ML Platform vision, translating Ads pain points into reusable platform capabilities where appropriate.\n Define architecture and technical standards for ML feature and training-data systems across batch/streaming computation, backfills, lineage, quality, observability, and online/offline consistency.\n Stay close to ML engineers and platform customers to identify high-leverage friction points and improve day-to-day development velocity.\n Build platform abstractions and workflow automation that make ML development faster, safer, more reliable, and more self-service.\n Over time, extend the platform strategy into serving and online experimentation workflows, creating a more seamless offline-to-online ML development experience.\n Partner across Ads, ML Platform, Data Platform, modeling, product, and engineering teams to clarify ownership, resolve ambiguity, and drive durable execution.\n Mentor Staff and senior engineers, raise the architecture and operational bar, and help grow the next generation of technical leaders.\n \n Who You Might Be \n \n You have 8+ years of experience in infrastructure, distributed systems, ML platforms, data platforms, or large-scale backend systems.\n You have 4+ years building or operating production ML infrastructure, feature platforms, training data systems, experimentation systems, or large-scale data pipelines.\n You have led broad, ambiguous, multi-team platform initiatives from strategy through adoption.\n You have built platforms used directly by ML engineers, data scientists, or product teams developing production ML systems.\n You have deep experience in ML platform, feature platform, training data, experimentation, developer infrastructure, or distributed data infrastructure.\n You have worked with distributed data and compute systems such as Spark, Flink, Kafka, Ray, Airflow, Iceberg, Kubernetes, BigQuery, Snowflake, Databricks, or similar technologies.\n You can balance urgent customer needs with durable long-term architecture and reusable platform patterns.\n You influence senior engineers and leaders through clear technical reasoning, RFCs, design reviews, decision frameworks, and operating mechanisms.\n You are excited to shape how production ML systems are built, scaled, and operated, not only how models are trained.\n \n Benefits: \n \n Comprehensive Healthcare Benefits and Income Replacement Programs\n 401k with Employer Match\n Global Benefit programs that fit your lifestyle, from workspace to professional development to ca","salary_min":292500,"salary_max":409500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["healthcare","distributed-systems","data-pipeline","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/reddit/jobs/8157275","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T18:40:31Z","expires_at":"2026-09-29T13:38:59.415338Z","created_at":"2026-08-25T19:40:19.020618Z","updated_at":"2026-08-30T13:38:59.553319Z","company_name":"Reddit","company_slug":"reddit","company_logo_url":"https://www.google.com/s2/favicons?domain=www.reddit.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a85f6a22-2c3d-4d63-bc92-fb6bab844254"},{"id":"9a42e317-7954-4330-9e7d-59cad3214bb9","company_id":"8115806a-6d9c-48b9-9a92-5eb180bbd1ef","title":"Applied Research Scientist, AI Research","slug":"applied-research-scientist-ai-research-428d0a90","description":"Descript's Research team builds the models behind the product's most distinctive features: Video Regenerate and lipsync, video translation, zero-shot voice and roomtone cloning, and Studio Sound. We don't build general-purpose generative models. We pick specific problems in the editing workflow and build specialized models for them. This isn't research for its own sake. Everything we build is meant to ship, and most of it has, going from prototype to a production feature used by millions of creators within months.\n This role is focused on multimodal understanding: training models to perceive edited media the way a human video editor does. Underlord, our AI editing agent, reasons about a project largely through a textual representation of it. Giving it direct perception of the media it's working on is what will let it judge its own output and reason about the creative choices in an edit, not just the structure of a project. It's also an open research problem, since there's no settled way to represent or evaluate editorial craft, whether a cut lands or whether the pacing works. We have a unique dataset to work with.\n Some recent work from the team:\n \n Audio editing by latent inpainting : regenerating a masked span of speech \n Video Regenerate : regenerating a speaker's lower face to match new or translated audio\n Jumpcut Smoothing : generating a bridge across a cut so the join plays like a continuous take\n Anchored Tree Sampling : tree-based imputation that bounds drift in long video generation\n PoDAR : disentangling power from semantics in audio latents to make them easier to model\n \n More at descript.com/research .\n What you'll do\n \n Multimodal understanding: build vision-language systems that let Descript's agentic editing features reason over the visual and audio content of a project.\n Evaluation: design the benchmarks and evals that make editorial quality measurable, and that balance quality against cost and latency.\n Data: build the datasets your work depends on, including synthetic data generation where real examples don't exist at scale.\n Training: train specialized models from scratch or fine-tune existing foundation models, whichever gets the capability we need.\n Shipping: take models from prototype to production with the agent and engineering teams.\n Direction-setting: identify the next research direction that should become a Descript feature, not just a paper. More senior candidates should expect to own this directly; more junior candidates will grow into it.\n Publishing: take your work to academic venues if you'd like. We support it, but it isn't a requirement of the role.\n \n What you bring\n Required\n \n Proven ability to design and implement deep learning algorithms, demonstrated by publications, open-source work, or models you've shipped.\n Strong programming skills and deep fluency in PyTorch.\n A track record of generating new ideas in machine learning. You produce more ideas than you can implement, and once an experiment setup is established, you can run and evaluate many of them quickly rather than being bottlenecked on infrastructure.\n Strong experimental judgment. You test ideas fast, and you're honest with yourself and the team about which ones don't pan out.\n Clear written and verbal communication, including when a direction isn't working, so the team doesn't waste time following a lead that's already dead.\n A PhD or Master's in deep learning or a related field, or equivalent experience. We care about the track record more than the credential.\n \n At least one of the following must be true:\n \n Lead or first author of an accepted publication in a top venue: CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, or similar.\n Played a key role in shipping a production feature with deep learning as a core component.\n \n More senior candidates (Senior and Staff) should also bring a track record of owning research direction rather than executing a plan handed to them, and experience mentoring or technically leading other researchers or engineers.\n Where breadth helps\n Direct experience in multimodal understanding is welcome but not required, and we don't require domain-specific expertise in computer vision or speech and audio. Our team spans both, and strong general deep learning ability transfers. We hire against the bar above, and then expect you to grow into the domain. Depth in any of these is a strong signal:\n \n Vision-language models and multimodal understanding.\n Generative modeling for video, audio, or images.\n Post-training, fine-tuning, and RL on large foundation models.\n Building evaluation systems for generative or agentic outputs where metrics resist clean definitions.\n Taking a research idea through to a shipped, production-facing feature.\n \n Compensation and benefits\n Base salary range: $197,000–$262,500, plus equity and benefits. Final offer amounts will carefully consider multiple factors, including prior experience, expertise, location, and level, and may vary from the amount above.\n  \n IMPO","salary_min":197000,"salary_max":262500,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","deep-learning","fine-tuning","computer-vision","pytorch","healthcare","agents","research"],"apply_url":"https://boards.greenhouse.io/descript/jobs/7967440003?gh_jid=7967440003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-25T00:18:24Z","expires_at":"2026-09-29T13:35:54.489992Z","created_at":"2026-08-25T18:27:44.358668Z","updated_at":"2026-08-30T13:35:54.624927Z","company_name":"Descript","company_slug":"descript","company_logo_url":"https://www.google.com/s2/favicons?domain=descript.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9a42e317-7954-4330-9e7d-59cad3214bb9"},{"id":"fef86a6f-88bb-4446-95f7-e78d16d7e82d","company_id":"a0000000-0000-0000-0000-000000000001","title":"Applied AI Engineer, Beneficial Deployments (Life Sciences)","slug":"applied-ai-engineer-beneficial-deployments-life-sciences-59ac98a0","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About Beneficial Deployments Beneficial Deployments ensures AI reaches and benefits the communities that need it most. We partner with nonprofits, foundations, and mission-driven organizations to deploy Claude in education, global health, economic mobility, and life sciences — focusing on raising the floor for those who need it most.\n About the Role We're looking for an Applied AI Engineer to join our Beneficial Deployments team, focused on maximizing the impact of Claude in the life sciences. Our goal is ambitious: accelerate scientific progress from R\u0026D through translation by an order of magnitude. That means making Claude the go-to tool for the life sciences ecosystem from early discovery in academia to paradigm shifting biotech to reimaging pharma pipelines  — and building the technical infrastructure to back that up.\n You'll work directly with flagship research partners like The Howard Hughes Medical Institute (HHMI) and The Allen Institute, embedded in their scientific workflows. This isn't consulting from the outside — you'll be building alongside their engineers, prototyping agents that fit into real research pipelines, and developing the ecosystem-level tooling (MCP servers, benchmarks, reusable agent skills) that extends Claude's usefulness across the broader life sciences community. This role will be part of the founding Beneficial Deployments Applied AI team focused on bringing life sciences closer to the frontier.\n Responsibilities \n \n Partner deeply with flagship life sciences research institutions — understand their scientific workflows end-to-end, build hands-on with their engineering teams, and help take projects from early exploration to production systems integrated into how they do science day-to-day.\n Develop reusable ecosystem infrastructure, like MCP servers for domain-specific data sources (genomics platforms, literature databases, experimental repositories), instruments, scientifically-grounded benchmarks, and agent skills that other institutions can adopt without starting from scratch.\n Identify what's actually hard about deploying AI in life sciences (heterogeneous data, auditability requirements, the prototype-to-trust gap) and feed those findings back to product, engineering, and research.\n Create technical content and documentation that lets partners self-serve, so what works for one institution can scale globally without the same level of hand-holding.\n \n You Might Be a Good Fit If You Have: \n \n Deep research experience in life sciences, biomedical research, or scientific computing. Bonus if you've studied genomics, neuroscience, or drug discovery specifically and are comfortable getting deeply technical with academics.\n Experience building LLM-powered tools or applications: prompting, context engineering, agent architectures, evaluation frameworks.\n Builder credibility from shipping production code as a software engineer, forward-deployed engineer, or technical founder.\n A scrappy mentality–comfortable wearing multiple hats, building from scratch, driving clarity in ambiguous situations, and doing whatever it takes to further the mission.\n The annual compensation range for this role is listed below. \n For sales roles, the range provided is the role’s On Target Earnings (\"OTE\") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.\n Annual Salary:\n $280,000 — $320,000 USD \n Logistics \n Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience\n Required field of study:  A field relevant to the role as demonstrated through coursework, training, or professional experience\n Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position\n Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.\n Visa sponsorship:  We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.\n We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed.  Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourse","salary_min":280000,"salary_max":320000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["healthcare","fine-tuning","alignment","llm"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5021015008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-24T22:31:29Z","expires_at":"2026-09-29T13:30:13.399752Z","created_at":"2026-08-25T18:26:11.30816Z","updated_at":"2026-08-30T13:30:13.543553Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/fef86a6f-88bb-4446-95f7-e78d16d7e82d"},{"id":"b9aa4c99-030d-4e40-9e6f-9761f83b7938","company_id":"308b7777-69e1-49db-ad79-3912d6c6e648","title":"Staff Software Engineer, Marketplace Acquisition","slug":"staff-software-engineer-marketplace-acquisition-e55d1f4b","description":"Our Mission \n Healthcare should work for patients, but it doesn’t. In their time of need, they call down outdated insurance directories. Then wait on hold. Then wait weeks for the privilege of a visit. Then wait in a room solely designed for waiting. Then wait for a surprise bill. In any other consumer industry, the companies delivering such a poor customer experience would not survive. But in healthcare, patients lack market power. Which means they are expected to accept the unacceptable. \n  \n Zocdoc’s mission is to give power to the patient. To do that, we’ve built the leading healthcare marketplace that makes it easy to find and book in-person or virtual care in all 50 states, across +200 specialties and +12k insurance plans. By giving patients the ability to see and choose, we give them power. In doing so, we can make healthcare work like every other consumer sector, where businesses compete for customers, not the other way around. In time, this will drive quality up and prices down.  \n  \n We’re 18 years old and the leader in our space, but we are still just getting started. If you like solving important, complex problems alongside deeply thoughtful, driven, and collaborative teammates, read on. \n  \n Your Impact on our Mission \n As a Staff Software Engineer on the Marketplace Acquisition team at Zocdoc, you'll turn ideas into reality fast — prototyping, iterating, and shipping high-impact experiences that help patients discover and access care. You'll own the systems behind Zocdoc's patient acquisition and engagement, keeping everything at the top of the funnel stable, scalable, and fast. That means driving the evolution of our SEO infrastructure, which powers thousands of patient-facing pages; iterating on provider profile and practice page designs to create seamless, trustworthy experiences; and building the APIs and services that make patient-facing data fast and reliable at scale.\n You'll also shape how we build. Zocdoc is making a company-wide push to drive engineering through the lens of AI, and you'll be an active participant in it — bringing AI into your day-to-day development, contributing to the standards, guardrails, and review practices the organization is building, and raising the ceiling on what a small team can ship. Multiplying the output of the engineers around you is as much a part of this role as the code you write yourself.\n You'll work closely with Design, Product, and Marketing to align on strategy and deliver measurable impact, all while fostering a culture of technical excellence, mentorship, and innovation that keeps Zocdoc at the forefront of healthcare technology.\n  \n You’ll enjoy this role if you are… \n \n Driven by the opportunity to impact healthcare positively, our mission is to create a seamless, efficient, and deeply human experience\n Product-driven with a relentless focus on user needs\n Passionate about engineering excellence, with a strong focus on promoting best practices in code quality, testing, and long-term maintainability across teams and the organization\n Demonstrates strong ownership of their technical domain and invests in mentoring others by sharing knowledge and best practices across teams\n \n  \n Your day to day is… \n \n Leading the technical direction of Zocdoc’s acquisition platform, enhancing system stability and user experience. Guiding technical discussions, ensuring decisions are scalable and dependable, and aligning infrastructure with the team’s broader mission\n Building scalable APIs and microservices that power frictionless data access and informed patient decision-making\n Collaborating with design counterparts to iterate on user experiences and improve the overall customer journey\n Proactively engaging with product counterparts to align on vision, strategy, and execution, ensuring projects stay on track and deliver business value\n Mentoring engineers and driving team excellence through coding standards, automation, and continuous improvement\n Leading bold innovation initiatives centered on AI, leveraging emerging data sources and cutting-edge architectures to position Zocdoc as a leader in healthcare technology\n \n  \n You’ll be successful in this role if you have… \n \n Owned and evolved complex, user-facing platforms end-to-end, balancing rapid delivery with long-term technical vision to ensure scalable, maintainable, and impactful experiences\n Designed and built performant systems with search engine optimization (SEO) and page speed as top priorities, ensuring fast, reliable, and discoverable patient experiences at scale\n Architected full-stack solutions spanning backend APIs, AWS-based infrastructure, and React systems that are modular, reusable, and leveraged across teams\n Integrated with third-party data sources and content management systems, such as Contentful, to deliver dynamic, flexible, and content-rich user experiences\n Leveraged large language model (LLM) systems to transform raw user data into actionable in","salary_min":180000,"salary_max":265000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["healthcare","llm","search","microservices"],"apply_url":"https://job-boards.greenhouse.io/zocdoc/jobs/8082085","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-24T19:28:42Z","expires_at":"2026-09-29T13:49:10.506575Z","created_at":"2026-08-25T18:33:36.50581Z","updated_at":"2026-08-30T13:49:10.636727Z","company_name":"ZocDoc","company_slug":"zocdoc","company_logo_url":"https://www.google.com/s2/favicons?domain=zocdoc.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/b9aa4c99-030d-4e40-9e6f-9761f83b7938"},{"id":"30b225f4-4652-4168-a97b-c7af2308a23d","company_id":"e8dfc4ee-9649-4fd0-9c16-90d38a1954e1","title":"Staff Security Engineer, Proactive Security - AI","slug":"staff-security-engineer-proactive-security-ai-de8a9beb","description":"About the Team \n At DoorDash we’re building the industry’s most scalable and reliable delivery network to support our three-sided marketplace of consumers, merchants, and Dashers. Security Engineering is paramount to the success of our business, and DoorDash Security aspires to be one the world’s most admired Security Engineering team. We are committed to building the world's most trusted on-demand, logistics engine for delivery! We're expanding our team of great minds to help us secure and maintain a 24x7, no downtime, global infrastructure system that powers DoorDash’s multi-sided marketplace of consumers, merchants, and drivers.\n About the Role \n Our Proactive Security Engineering team is looking for a Staff Security Engineer, Proactive Security to execute on AI Security Product Engineering following a forward deployed engineering Pod model.\n You will be a part of our inclusive, collaborative forward deployed engineering team responsible for building “paved road” Security Product controls directly into our AI surfaces for our Customer, Merchant and Dasher products to ensure a safe, secure and resilient delivery network. This is not a classic Product Security role performing reviews and operating platform products, this is a forward deployed model where we operate in Pods that focus on domain code bases to build and ship AI Security Products including Hardened Product Agents, AI Guardrails, MCP Gateways and many upcoming AI Hardening initiatives. \n This is a US remote position reporting directly to the Manager of our Proactive Security Engineering team. \n You’re excited about this opportunity because you will… \n \n Co-lead the technical direction and roadmap for secure and responsible building of AI Security Products at DoorDash.\n Partner cross-functionally with Product Engineering, Legal, Security Engineering Platform, Data teams and XFN partners to build “paved road” proactive security controls that enable secure by design AI products into DoorDash eco-system. Examples of AI Security Products this team has built include Hardened Product Agents, AI Guardrails, MCP Gateways and many upcoming AI Hardening initiatives. \n Execute rigorous cross-brand AI enabled vulnerability discovery, multi-level harnesses and automated remediation to protect the company against Mythos-era equipped adversaries. \n Mentor and coach earlier career engineers, setting and enforcing exceptional standards for Operational Excellence and Software Engineering.\n \n We’re excited about you because… \n \n 10+ years of experience as a Security Product Engineer at an Internet scale organization of demonstrated technical leadership building outcomes at global scale.\n Master’s degree in Computer Science, Security Engineering, a related field or equivalent work experience.\n Embed with product teams to design, build, and deploy security controls for consumer, merchant, and Dasher products.\n Develop reusable “paved road” solutions that help teams build secure AI products by default.\n Partner with Product Engineering, Legal, Data, Security Platform, and other teams to translate security and regulatory requirements into practical engineering controls.\n Demonstrated technical leadership in designing scalable, AI enabled and ergonomic Security Review threat modeling.\n Hands-on experience securing LLM or agentic systems, or demonstrated ability to move quickly into the space from adjacent depth in authorization, sandboxing, or untrusted input handling.\n Demonstrated builder in one or more object oriented languages (e.g. Go, Java) designing technical Security Engineering controls and processes to meet business and regulatory requirements. \n Exceptional problem solving of complex, systemic issues that require audacious thinking, rigor and creativity.\n \n \n Exceptional analytical and investigative abilities with hands-on experience leading root cause analysis for security incidents and driving long term roadmaps to remediate.\n \n \n Exceptional verbal and written communication skills - you will confidently shape and lead the Security Product Engineering within your assigned AI Security domain across core engineering and product teams to security preserving control outcomes. \n \n Why You’ll Love Working at DoorDash \n \n We are leaders - Leadership is not limited to our management team. It’s something everyone at DoorDash embraces and embodies.\n We are doers - We believe the only way to predict the future is to build it. Creating solutions that will lead our company and our industry is what we do -- on every project, every day. \n We are learners - We’re not afraid to dig in and uncover the truth, even if it’s scary or inconvenient. Everyone here is continually learning on the job, no matter if we’ve been in a role for one year or one minute.\n We are customer-obsessed - Our mission is to grow and empower local economies. We are committed to our customers, merchants, and dashers and believe in connecting people with p","salary_min":193800,"salary_max":285000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"lead","tags":["llm","security","agents","cloud","healthcare","fine-tuning"],"apply_url":"https://job-boards.greenhouse.io/doordashusa/jobs/8154315","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-24T18:30:40Z","expires_at":"2026-09-29T13:49:21.802144Z","created_at":"2026-08-26T13:49:31.761186Z","updated_at":"2026-08-30T13:49:21.930778Z","company_name":"DoorDash","company_slug":"doordash","company_logo_url":"https://www.google.com/s2/favicons?domain=doordash.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/30b225f4-4652-4168-a97b-c7af2308a23d"},{"id":"d4653f80-c2d2-4f90-b750-70a300947a71","company_id":"861968d1-d9f8-4217-9873-ce4b24851abc","title":"Manager of Data Science Production Engineering, Data Engineering \u0026 Delivery","slug":"manager-of-data-science-production-engineering-data-engineering-delivery-a1a2ddc4","description":"This is an exciting opportunity to lead a Data Engineering \u0026 Delivery (DED) team at Natera, a global leader in precision medicine and genomics testing.  As a Manager of the DED team inside our Data Science Production Engineering (DSPE) department, you will have the opportunity to work with Natera's diverse and ultra-large data sets (up to PB size), develop innovative solutions with the latest information and cloud technologies, and make real impact by providing timely, accurate, and robust data products and data delivery/automation systems to support Natera's Lab Operations and Genetic Counselor/Lab Director teams, and ultimately impact patients' medical outcomes.\n PRIMARY RESPONSIBILITIES:  \n Leadership \n \n Lead a Data Engineering \u0026 Delivery (DED) team, collectively develop and maintain the data infrastructure, data ingestion solutions, ETL pipelines, robust data products, and data delivery solutions, for both production support and DSPE internal applications.\n Manage the Data Engineering \u0026 Delivery (DED) team, to achieve the timely and efficient delivery of robust data products and systems that can meet DSPE business needs and project requirements.\n Measure, report, and maintain/improve operational effectiveness.\n Train and coach team members on new technologies, procedures, and guidelines/best practices.\n \n Technical \n \n Lead the Data Engineering \u0026 Delivery (DED) team, collectively develop and maintain the data infrastructure, data ingestion solutions, ETL pipelines, robust data products, and data delivery solutions, for both production support and DSPE internal applications\n Translate DSPE's business needs and project requirements into technical specifications and implementation plans.\n Working with DSPE leadership teams, create design documents that can be efficiently implemented and maintained, for data system architecture, data ETL pipeline, data delivery solution, and other data systems/tools/components.\n Contribute to key development, testing, deployment, validation, maintenance, and update activities on data products and data systems/tools/components, as well as data delivery tasks.\n \n Quality, Compliance, and Documentation \n \n Improve and enforce operating procedures for compliance, quality, and efficiency.\n Create training materials, and contribute to training activities, on DSPE Data Engineering \u0026 Delivery (DED) team owned data products and data systems.\n \n Cross-Functional \n \n Engage proactively and directly with internal and external stakeholders to align development roadmaps, resolve dependencies, and exchange performance metrics.\n Represent the Data Engineering \u0026 Delivery (DED) team in stakeholder meetings.\n \n QUALIFICATIONS: \n \n Masters degree in Statistics, Data Science, Bioinformatics, Computer Science, Mathematics, Management Science, Operational Research, or other related fields. Doctorate degrees are a plus.\n Minimal 5 years of relevant industry experience for candidates with a Master's Degree.  Minimal 2 years of relevant industry experience for candidates with a Doctorate degree.\n Minimal 2 years of working experience in a highly regulated environment, e.g., CLIA and/or FDA compliant settings.\n Minimal 2 years of management experience leading a Data Engineering team, a Data Production/Delivery team, or a Data Analytics team, with demonstrable evidence of leadership and team management skills.\n \n KNOWLEDGE, SKILLS, AND ABILITIES: \n \n Strong proficiency in SQL and Python programming languages. Proficiency in R is a plus.\n Proficiency in data analysis and statistical techniques.\n Proficiency in data visualization tools (e.g., Tableau, Power BI, AWS QuickSight).\n Strong SQL skills in developing robust and maintainable queries to extract and/or aggregate data from complex data sources.\n Attention to detail and a commitment to data accuracy.\n Proficiency in building data products, e.g., data aggregation, extraction, transformation, and QC. Past working experience in dbt is a plus.\n Excellent problem-solving and critical-thinking abilities.\n Working knowledge of genomics and bioinformatics workflows. Human genetics knowledge is a plus.\n Proficiency in Git workflow and version control systems like GitHub and/or GitLab.\n Working experience with healthcare data, electronic health records (EHR), and clinical terminology is a plus.\n Ability to work collaboratively in a cross-functional team environment.\n Good documentation practices and coding style.\n Strong verbal and written communication skills.\n Strong interpersonal skills.\n Strong integrity.\n \n Compensation \u0026 Total Rewards  \n This range reflects a good-faith estimate of the base pay we reasonably expect to offer at the time of  hire. Final compensation will vary based on experience, qualifications, and internal equity considerations. \n This position is also eligible for additional compensation and benefits through Natera’s robust Total Rewards program, including: \n \n \n Annual performance incentive bonus \n \n Long-term equity awar","salary_min":139900,"salary_max":174900,"location":"San Carlos, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["cloud","data-pipeline","healthcare","data-science","data-engineering"],"apply_url":"https://job-boards.greenhouse.io/natera/jobs/6150570004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T20:13:10Z","expires_at":"2026-09-29T13:40:54.756368Z","created_at":"2026-08-25T18:29:44.00758Z","updated_at":"2026-08-30T13:40:54.89509Z","company_name":"Natera","company_slug":"natera","company_logo_url":"https://www.google.com/s2/favicons?domain=natera.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d4653f80-c2d2-4f90-b750-70a300947a71"}],"page":1,"per_page":20,"total":1178,"total_is_exact":true,"total_pages":59}