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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":["agents","llm","rag","embeddings","payments","healthcare"],"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":"2026-09-28T13:31:52.334372Z","created_at":"2026-04-13T09:36:56.004203Z","updated_at":"2026-08-29T13:31:52.484021Z","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":["healthcare","embeddings","agents","llm","rag","payments"],"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":"2026-09-28T13:31:51.4745Z","created_at":"2026-04-13T09:36:54.973831Z","updated_at":"2026-08-29T13:31:51.624997Z","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":"5cda7f2c-d00e-45ae-bf4a-b6e6811a6e5a","company_id":"7f070aa1-7d20-4bbe-b6d2-68769923074e","title":"Principal Enterprise Technology Architect","slug":"principal-enterprise-technology-architect-e98bf7db","description":"Crusoe is on a mission to accelerate the abundance of energy and intelligence. As the only vertically integrated AI infrastructure company built from the ground up, we own and operate each layer of the stack — from electrons to tokens — to power the world's most ambitious AI workloads. When you join Crusoe, you join a team that is building the future, faster.\n\n\n\nWe're in the midst of the greatest industrial revolution of our time. The demand for AI compute is boundless, and power is a bottleneck. We're solving that — with an energy-first approach that makes AI infrastructure better for the world and faster for the people innovating with AI.\n\n\n\nWe're looking for problem-solving, opportunity-finding teammates with a sense of urgency, who believe in the scale of our ambition and thrive on a path not fully paved — people who want to grow their careers alongside a team of experts across energy, manufacturing, data center construction, and cloud services.\n\n\n\nIf you want to do the most meaningful work of your career, help our customers and partners advance their AI strategies, and be part of a high-performing team that believes in each other, come build with us at Crusoe.\n\n\n\nAbout the Role:\n\nWe are looking for a Principal Enterprise Technology Architect to own the technical vision for how our internal business systems connect, scale, and evolve. This is a newly created senior Individual Contributor role: you will be the highest-ranking technical voice in our Enterprise Technology organization, setting the architectural standard that guides our team of experienced system administrators.\n\n \n\nCrusoe is at an inflection point. We have mature, capable platforms running Finance (Oracle Fusion, Coupa, Sage Intacct), Construction and Operations (Procore, Oracle Primavera), and People (Rippling, Ashby), but they operate largely as islands. Your mandate is to design the unified architecture that connects them: defining master data models, engineering a scalable and increasingly event-driven integration layer, and building the governance frameworks (including how AI is responsibly introduced into these systems) that take us from startup agility to enterprise maturity.\n\n \n\nThis is a greenfield architecture role first. You will spend the majority of your time designing systems, producing ERDs, context diagrams, and sequence flows, before a single line of configuration is written. This role does not carry formal people-management responsibility, though as a Principal (P6) you may guide contributors indirectly on complex initiatives. You will serve as the integration and architecture subject matter expert that a team of senior administrators pulls in on complex, cross-system initiatives, and as a voice in Architecture Review Board discussions on major platform changes.\n\n \n\nThis role partners with, rather than replaces, existing domain owners: the IT Architect retains ownership of iPaaS design and governance, the Identity Lead retains ownership of IAM/PAM and access governance, and the AI \u0026 Automation Staff Engineer retains ownership of AI governance and architecture. This role's mandate is enterprise-wide data-model and integration-pattern design, done in partnership with those owners.\n\n\n\nWhat You'll Be Working On:\n\n \n\n - Greenfield Architecture \u0026 System Design\n   \n   - Lead technical discovery for all major system initiatives, producing high-fidelity artifacts — ERDs, system context diagrams, data flow maps, and sequence diagrams — that serve as the source of truth for implementation\n   \n   - Assess current platform limitations and define the path forward, including when to optimize, when to re-platform, and when to build a custom integration layer\n   \n   - Serve as the primary technical evaluator during software procurement, vetting vendors on API robustness, data model flexibility, and security compliance — not just features\n   \n   - Identify and document integration debt across the current-state architecture and develop a prioritized roadmap to address it\n   \n   - Participate in Architecture Review Board discussions, ensuring major system changes align with enterprise standards and reference architecture\n\n - Master Data \u0026 Integration Strategy\n   \n   - Partner with platform SMEs and administrators to define a unified approach to master data across the organization\n   \n   - Partner with the IT Architect and platform SMEs who own our iPaaS integration environment today, co-developing reusable integration patterns, error-handling frameworks, and self-healing workflows that raise the bar without displacing existing ownership\n   \n   - Drive integration architecture toward API-first, event-driven patterns (REST, webhooks/pub-sub) where they improve reliability and reduce latency over batch processing\n   \n   - Define how internal systems authenticate and communicate, with strict enforcement of secure API standards (OAuth 2.0, REST/SOAP) across all integrations\n\n - AI \u0026 Intelligent Automation\n   \n   - Partner with t","salary_min":225000,"salary_max":255000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"principal","tags":["embeddings","code-generation","llm","agents","cloud"],"apply_url":"https://jobs.ashbyhq.com/crusoe/582f3d5e-2ee6-47b7-9cfc-a9691cfa4bca/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-27T23:24:29.385Z","expires_at":"2026-09-28T13:36:18.261736Z","created_at":"2026-08-29T13:36:18.423689Z","updated_at":"2026-08-29T13:36:18.423689Z","company_name":"Crusoe","company_slug":"crusoe","company_logo_url":"https://www.google.com/s2/favicons?domain=crusoe.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/5cda7f2c-d00e-45ae-bf4a-b6e6811a6e5a"},{"id":"e17eda01-e317-4c5f-9dae-d8e3404b1b2e","company_id":"ec4a8bb4-3840-4054-8ccd-77e81db037af","title":"Data Scientist/Senior Data Scientist","slug":"data-scientistsenior-data-scientist-565352fb","description":"C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise. Learn more at: C3 AI \n As a member of the C3 AI Data Science team , you will work with some of the largest companies on the planet helping them build the next generation of AI-powered enterprise applications on the C3 AI Platform. You will work directly with data scientists, AI engineers, and subject matter experts to design and deploy AI capabilities that give our customers the information they need to make better decisions and accelerate their digital transformation. You will identify the right AI approaches for each problem and implement them on the C3 AI Platform so they run reliably at enterprise scale.\n Qualified candidates will have deep knowledge of modern AI and ML techniques — including large language models, agentic systems, and classical statistical methods — along with a clear understanding of their limitations and how to adapt them to large-scale production environments. Some travel is expected.\n Note: This is a client-facing position which requires travel. Candidates should have the ability and willingness to travel based on business needs. \n Responsibilities: \n \n Lead the research, design, implementation, and deployment of AI models, agentic solutions, and optimization algorithms for enterprise applications on the C3 AI Platform.\n Partner with C3 AI customers to build and scale their own AI applications on the Platform.\n Contribute to the design and implementation of new AI capabilities within the C3 AI Platform.\n Analyze model performance across enterprise deployments, diagnose issues such as poor recall or false positive rates, and recommend targeted improvements.\n Collaborate with data engineers and subject matter experts from C3 AI and customer teams to source, validate, and correctly leverage new data assets.\n \n Qualifications: \n \n MS or PhD in Computer Science, Electrical Engineering, Statistics,   Operations Research, or a related field.\n Hands-on AI experience spanning generative AI, agentic systems, supervised and unsupervised learning, and classical regression and classification.\n Strong mathematical foundation in linear algebra, calculus, probability, and statistics.\n Experience building and deploying models at scale in distributed or cloud-native environments.\n Ability to drive projects independently and collaborate effectively across technical and non-technical teams.\n Sharp, motivated, and focused on making a real impact.\n Excellent verbal and written communication skills.\n \n Preferred Qualifications: \n \n Proficiency in Python; experience with JavaScript, Java, or Scala is a plus.\n Familiarity with LLM frameworks (e.g., LangChain, LlamaIndex), vector databases, or RAG architectures.\n A portfolio of AI projects (GitHub, publications, or open-source contributions) is a plus.\n C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. \n California Base Pay Range\n $136,000 — $183,000 USD \n C3 AI is proud to be an Equal Opportunity and Affirmative Action Employer. We do not discriminate on the basis of any legally protected characteristics, including disabled and veteran status.","salary_min":136000,"salary_max":183000,"location":"Redwood City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","generative-ai","rag","embeddings","llm","data-science"],"apply_url":"https://c3.ai/job-description/8751111002?gh_jid=8751111002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T17:07:29Z","expires_at":"2026-09-28T13:40:51.985366Z","created_at":"2026-08-27T13:40:52.550205Z","updated_at":"2026-08-29T13:40:52.13633Z","company_name":"C3 AI","company_slug":"c3-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=c3.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e17eda01-e317-4c5f-9dae-d8e3404b1b2e"},{"id":"82dec910-1062-4275-8ca4-cb2a591a1dd1","company_id":"5d6de1f6-4d6c-463b-8a2b-a5caeadb97b4","title":"Senior Software Engineer - Build, NYC","slug":"senior-software-engineer-build-nyc-e267b790","description":"Astronomer empowers data teams to bring mission-critical software, analytics, and AI to life and is the company behind Astro, the industry-leading unified DataOps platform powered by Apache Airflow®. Astro accelerates building reliable data products that unlock insights, unleash AI value, and powers data-driven applications. Trusted by more than 800 of the world's leading enterprises, Astronomer lets businesses do more with their data. To learn more, visit  www.astronomer.io http://www.astronomer.io.\n\n\n\n\nABOUT THIS ROLE\n\nApache Airflow is one of the most popular open-source data platform tools. It powers the data platforms at nearly every large company and fast-growing startups: Airbnb, Uber, OpenAI, Anthropic, Nike, Capital One, Disney all use Airflow extensively. At Astronomer, we’re the largest contributors to the project and are building commercial products around Airflow to make it easier to use, run, and scale.\n\n\n\nWe’re in a unique position: as the company behind Apache Airflow, we see data as it moves across entire organizations—from raw ingestion to production dashboards, machine learning models, and AI products. Leveraging this vantage point, our R\u0026D team is developing a global context layer for data—an intelligence layer that powers search and discovery, code generation for data and analytics, and automated root cause analysis. LLMs are already quite good at writing Python and SQL code against data platforms; we think this context layer will give them the metadata necessary for data practitioners everywhere to use LLMs effectively.\n\n\n\nAs a Software Engineer on this team, you’ll help design and build this foundation and the applications around it. You’ll work on some of the hardest and most exciting challenges in data—search, information retrieval, and AI for data pracitioners—while collaborating with a small, highly skilled team that values velocity, creativity, and impact. This role sits at the intersection of applied research, software engineering, and product: we think it takes someone who can work across the stack to build, release, and scale products successfully in this space.\n\n\n\nHybrid Work Model: For this role, you will embrace a flexible hybrid work model with at least 3 days per week in our New York City office.\n\n\n\n\n\nWHAT YOU GET TO DO:\n\n - Shape the future of AI for data engineering - build intelligent systems that understand, reason about, and optimize the flow of data across entire organizations.\n\n - Design and engineer the brain of Astronomer’s context layer, crafting components that power data modeling, semantic search, retrieval, and code generation.\n\n - Push the boundaries of applied AI - experiment with LLMs, embeddings, and cutting-edge retrieval techniques to create developer tools that deliver insights to you and our customers.\n\n - Turn research into reality - work side by side with R\u0026D and product teams to bring early AI concepts to life in the product experience.\n\n - Solve high-impact information retrieval and search challenges at a global scale, leveraging Astronomer’s unparalleled visibility into data pipelines across industries.\n\n - Influence the technical vision and architecture for the next generation of AI-driven data products.\n\n - Represent Astronomer in the community - through open-source contributions, technical talks, and publications that showcase our leadership in AI and data innovation.\n\n\n\n\nWHAT YOU BRING TO THE ROLE:\n\n - 5-8 years of software engineering experience with Python or Go\n\n - Empathy for users, and a deep interest in improving the workflows of data professionals.\n\n - Familiarity with early-stage product development; comfortable working with ambiguity in a fast-changing field.\n\n - Experience with LLMs, vector databases, embeddings, or other applied AI areas—or a strong desire to dive in.\n\n - A creative, experimental mindset: you enjoy exploring uncharted areas, validating hypotheses, and learning through iteration.\n\n - Strong collaboration and communication skills—you can explain complex systems clearly to both technical and non-technical audiences.\n\n - A collaborative approach and comfort working in an evolving, research-driven environment where ideas move quickly.\n\n\n\n\nBONUS POINTS IF YOU HAVE:\n\n - A passion for AI systems for data, developer tools, or machine learning infrastructure.\n\n - Familiarity with Apache Airflow or other orchestration tools.\n\n - Demonstrated contributions to open source projects.\n\n - Experience in search, IR, or large-scale data infrastructure.\n\n - Exposure to early-stage startups or R\u0026D organizations where ambiguity is the norm.\n\n - Experience building out agentic systems on top of frontier models.\n\n\n\nThe estimated total compensation for this role ranges from $210,000 - $250,000 based on leveling and geography, along with an equity component and a comprehensive benefits package. This range is merely an estimate; actual compensation may deviate from this range based on skills, experience, and qualific","salary_min":210000,"salary_max":250000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","code-generation","embeddings","agents","search","llm"],"apply_url":"https://jobs.ashbyhq.com/astronomer/3c72cd98-3493-4d30-8897-dc5e836db67e/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-26T08:13:00.068Z","expires_at":"2026-09-28T13:48:50.581489Z","created_at":"2026-08-26T13:47:11.23022Z","updated_at":"2026-08-29T13:48:50.739109Z","company_name":"Astronomer","company_slug":"astronomer","company_logo_url":"https://www.google.com/s2/favicons?domain=astronomer.io\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/82dec910-1062-4275-8ca4-cb2a591a1dd1"},{"id":"7cfc8bd1-ee86-44f8-a76b-20b093825232","company_id":"053355fc-0162-4bb9-b414-cbf7679ee9c8","title":"IT Platform and Automation Engineer","slug":"it-platform-and-automation-engineer-56eeaeee","description":"About Snorkel \n At Snorkel, we believe meaningful AI doesn’t start with the model, it starts with the data.\n We’re on a mission to help enterprises transform expert knowledge into specialized AI at scale. The AI landscape has gone through incredible changes since 2015, when Snorkel started as a research project in the Stanford AI Lab, to the generative AI breakthroughs of today. But one thing has remained constant: the data you use to build AI is the key to achieving differentiation, high performance, and production-ready systems. We work with some of the world’s largest organizations to empower scientists, engineers, financial experts, product creators, journalists, and more to build custom AI with their data faster than ever before. Excited to help us redefine how AI is built? Apply to be the newest Snorkeler!\n Job Description\n We're seeking a  IT Platform \u0026 Automation Engineer who treats internal infrastructure like a product—not a firefighting exercise. This is not a traditional helpdesk or \"break-fix\" role. You'll be the architect behind our internal employee experience, acting as the connective tissue between our office network, collaboration services, security stack, and core business systems (People Tech, CRM, and Engineering tools).\n If you prefer writing Python scripts over manually resetting passwords, and if you get excited about connecting Claude AI to Greenhouse via custom Slack workflows, we want to talk to you. \n This role is NOT: \n \n A traditional helpdesk position. You won't be resetting passwords or shipping laptops.\n A pure networking role. You'll touch networks, but automation is the priority.\n A machine learning engineer role. You'll experiment with AI, but you won't build vector databases or train models.\n \n   What You will Do\n Identity, Endpoint \u0026 Network (The Foundation) \n \n Identity \u0026 Access Management: Own our IdP (Okta/Auth0). Implement and automate SSO, MFA enforcement, and SCIM provisioning across all SaaS tools. Enforce zero-trust principles everywhere.\n Endpoint Lifecycle: Own the full hardware and MDM lifecycle. Automate device provisioning, configuration, and secure deployment using Jamf and Intune. Build zero-touch onboarding workflows. (Note: You will own the automation and security profiles; physical device shipping/fulfillment is handled by our IT Ops coordinators.) \n Network Engineering: Design, deploy, and maintain high-availability office networking (cloud-managed switching/routing, Wi-Fi) and secure remote access solutions (ZTNA/VPN) for a hybrid workforce. We prioritize automation-first engineers.\n \n Custom Integrations \u0026 Automation (The Builder Work) \n \n API Integrations: Architect and build custom integrations between our core SaaS stack—syncing data between Okta, Greenhouse, Notion, and our CRM to eliminate manual data entry.\n Workflow Orchestration: Own our internal automation layer. We currently use a mix of lightweight no-code tools (Zapier, App Script, AppSheet) and custom Python. We're actively phasing out low-code for mission-critical paths—you'll have permission to replace them with proper code. To be clear: this is a coding-heavy role. You'll spend the majority of your time writing code, not clicking in UIs. The no-code tools are placeholders—we expect you to replace or maintain them.\n Internal Tooling: Build and maintain internal dashboards and Slack apps that give employees self-service access to IT, HR, and facilities requests.\n \n AI \u0026 LLM Experimentation (The Innovation Work) \n \n AI Integrations: Review and assess connectors (MCP) if available. Otherwise, build lightweight API wrappers and prompt engineering pipelines to connect LLMs (Claude, OpenAI) to internal tools like Slack and Notion.\n R\u0026D Time: Dedicated time each sprint to experiment with new AI models and identify productivity gains for the company.\n \n Security Automation \u0026 Compliance (The Glue) \n \n Security Scripting: Write robust scripts (Python, Bash, PowerShell) to automate security monitoring, endpoint patch management, and compliance reporting.\n Alert Correlation: Architect centralized alerting pipelines by integrating EDR/SIEM webhooks into Slack via native integrations (CrowdStrike), filtering noise and surfacing only actionable security anomalies.\n Compliance Automation: Create automated audit trails, access reviews, and reporting to support SOC2 / ISO compliance efforts—no more manual spreadsheet work.\n \n Tech Stack Summary: Python, Okta/Azure AD, Jamf/Intune, Slack API, Greenhouse API, Notion API, Claude/OpenAI APIs, CrowdStrike, Meraki/cloud-networking, Google Workspace + GAM, Jira.\n  \n Who You Are\n  \n Foundation (Must-Have Baseline) \n \n Experience: 4+ years in IT Engineering, Systems Engineering, or Platform roles with a heavy emphasis on automation and APIs.\n Coding Proficiency: Advanced Python or JavaScript/Node.js. You treat your scripts like software—git, CI/CD, testing, and documentation are non-negotiable. Our current automation stack is built on Pyth","salary_min":120000,"salary_max":185000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["api-design","llm","generative-ai","embeddings","cloud"],"apply_url":"https://job-boards.greenhouse.io/snorkelai/jobs/6150440004","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-21T18:28:13Z","expires_at":"2026-09-28T13:34:10.005Z","created_at":"2026-08-25T18:27:04.327152Z","updated_at":"2026-08-29T13:34:10.161178Z","company_name":"Snorkel AI","company_slug":"snorkel-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=snorkel.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7cfc8bd1-ee86-44f8-a76b-20b093825232"},{"id":"95641443-c7f1-443a-b4d7-ef763360667d","company_id":"52f44519-9f93-4eac-ae0b-8be13e385ebe","title":"Machine Learning Engineer","slug":"machine-learning-engineer-a0756d7f","description":"MACHINE LEARNING ENGINEER\n\n \n\nYou'll build the ML behind Firecrawl — the models and the systems that serve them. That starts with search: training and shipping the ranking and relevance models for one of our fastest-growing products, then extending that work across extraction quality and LLM-driven features. You'll also own how we measure: A/B testing launches and building the experimentation frameworks the whole team ships against. If you ship models into production — whether your title says ML engineer or data scientist — this is for you.\n\n \n\nSalary Range: $210,000–$240,000/year\n\nEquity Range: Competitive equity — details shared during the process. \n\nLocation: San Francisco, CA (Hybrid, on-site required) \n\nJob Type: Full-Time \n\nExperience: 3+ years building ML or data-heavy systems in production \n\nVisa: Must be legally authorized to work in the United States. We're not able to sponsor visas right now, though that may change down the line.\n\n\n\n\nABOUT FIRECRAWL\n\nFirecrawl is the easiest way to turn the web into data AI agents can use. One API call converts any URL into clean, LLM-ready markdown or structured data - the boring-hard problem everyone building with LLMs eventually hits, solved.\n\nWe hit 8 figures in ARR in year one and more than doubled it in year two. We have 170k+ GitHub stars, and developers, agents, and category-defining AI companies build on us every day. Growth like this is rare, and we're just getting started.\n\nWe're a small team punching far above our weight. Everyone here owns a real piece of the product and company, end to end, and runs it themselves - no hiding behind process or headcount.\n\nThis is a place for people who want to work at the frontier: an AI company building the infrastructure other AI companies run on, not one bolting AI onto an existing product. We move fast, go deep, and are building the tools superintelligence will rely on to gather data from the web.\n\n\n\n\nWHAT YOU'LL DO\n\n - Improve ranking and relevance for Firecrawl Search — from feature engineering to model training to production\n\n - Build and tune models for learning-to-rank, query understanding, and LLM-driven retrieval\n\n - Extend ML across Firecrawl's products — extraction quality, content classification, and evaluation of LLM-driven features\n\n - Mine query logs and behavioral data at scale to find where our products win and where they fail\n\n - Build the data pipelines that turn web-scale crawl and query data into training data and features\n\n - Work hands-on with platform, search engineers and cloud DevOps to get models running fast and cheap in production\n\n - Design and formulate our testing strategy — the A/B testing frameworks and offline evaluation the team ships against\n\n - Partner on product launches across Firecrawl: define success metrics, run the experiments, and make the ship/no-ship call on evidence\n\n - Report on how releases perform post-launch and turn the findings into the next iteration\n\n\n\n\nWHAT WE'RE LOOKING FOR\n\n - You've shipped ML models into production systems and owned them after launch — deploying, monitoring, and retraining them, not handing them off\n\n - You have real ranking or relevance-modeling experience — learning-to-rank, recommendations, or search quality\n\n - You're comfortable in large, data-heavy systems: query logs, pipelines, and datasets that don't fit in memory\n\n - You write production-quality code (Python at minimum) and can work inside a real backend codebase\n\n - You're rigorous about measurement — you've designed and analyzed A/B tests and know when a lift is real\n\n - You can communicate results clearly to the team — what shipped, what moved, and what to do next\n\n\n\n\nNICE TO HAVE\n\n - MLOps experience — MLflow, experiment tracking, model registries, or feature stores; Kubernetes is a plus\n\n - Experience building or standardizing an experimentation framework at a previous company\n\n - Experience with embedding models, vector retrieval, or LLM-based relevance evaluation\n\n - Experience evaluating LLM outputs at scale — quality scoring, structured-extraction accuracy, or agent behavior\n\n - Spark or similar large-scale data processing experience\n\n\n\n\nWHAT WE'RE NOT LOOKING FOR\n\n - A pure statistician or analyst who needs an engineering team to productionize their work\n\n - Someone who wants to specialize narrowly and hand off everything else\n\n - Someone who optimizes for process over shipping\n\n\n\n\nA NOTE ON PACE\n\nWe operate at an absurd level of urgency because the window for what we're building won't stay open forever. If that excites you, keep reading. If it doesn't, no hard feelings — but this role probably isn't for you.\n\n\n\n\nBENEFITS \u0026 PERKS\n\n\n\n\nAVAILABLE TO ALL EMPLOYEES\n\n - Salary that makes sense — $210,000–$240,000/year, based on impact, not tenure\n\n - Own a piece — Gain competitive equity in what you're helping build\n\n - Generous PTO — 15 days mandatory, anything after 24 days, just ask (holidays excluded); take the time you need to rec","salary_min":210000,"salary_max":240000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","llm","data-pipeline","mlops","embeddings","search","machine-learning"],"apply_url":"https://jobs.ashbyhq.com/firecrawl/72f9dc1d-65db-48c9-b3d9-c6ccdb997006/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T21:40:10.101Z","expires_at":"2026-09-28T13:47:12.626429Z","created_at":"2026-08-25T18:32:19.563403Z","updated_at":"2026-08-29T13:47:12.783337Z","company_name":"Firecrawl","company_slug":"firecrawl","company_logo_url":"https://www.google.com/s2/favicons?domain=firecrawl.dev\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/95641443-c7f1-443a-b4d7-ef763360667d"},{"id":"42dee226-8fe7-4865-9781-15de96ca3cf0","company_id":"28040a6c-6f94-41a4-b15a-f2e4520188ff","title":"Forward Deployed Engineer","slug":"forward-deployed-engineer-a6d8ef8d","description":"About Dialpad Dialpad is the AI platform for customer experience, built to resolve customer problems in real time across voice and digital. Our AI agents learn from your best human agents and improve with every interaction, helping organizations understand their customers, deliver better experiences, increase operational efficiencies, and build a lasting competitive advantage. \n Unlike legacy systems built to route and answer, or standalone agentic bot vendors built to deflect, Dialpad was built to resolve. Our AI agents and human agents operate on a single platform with shared context, allowing Agentic AI to resolve issues, advance deals, and eliminate busywork through automation while seamlessly handing conversations to humans when needed, with full context preserved. \n Market-leading brands, including Randstad, Motorola Solutions, Netflix, the San Diego Padres, the Colorado Rockies Baseball Club, and Cal Athletics, trust Dialpad. Dialpad is backed by Andreessen Horowitz, GV, ICONIQ Capital, and T-Mobile. \n Being a Dialer At Dialpad, AI isn’t just a feature; it’s how our teams do their best work every day. We put powerful AI tools in every employee’s hands so they can move faster, think bigger, and achieve more. \n We believe every conversation matters. And we’ve built the platform that turns those conversations into insight and action, for our customers and ourselves. \n We look for people who are intensely curious and hold themselves to a high bar. Our ambition is significant, and achieving it requires a team that operates at the highest level. We seek individuals who embody our core traits: Scrappy, Curious, Optimistic, Persistent, and Empathetic . \n Your role The Forward Deployed Engineer (FDE) is a customer-embedded delivery engineer responsible for turning qualified AI opportunities into live, production-ready agent deployments. This role sits at the intersection of customer workflow design, applied AI engineering, enterprise integration, and production rollout. The core mission is to close the last-mile gap between platform capability and measurable customer outcomes by taking shaped opportunities from scoping through implementation and into the first production shift. \n You will work directly with customer stakeholders, internal delivery teams, and product partners to design, build, evaluate, deploy, and stabilize AI agents in real operating environments. This is a highly customer-facing, hands-on role for someone who can translate ambiguity into working systems and can move fluidly between technical depth and business impact. \n What you’ll do \n \n Convert prioritized use cases and pre-sales assumptions into a clear delivery scope, technical plan, and phased implementation approach. \n Work directly with customer technical and operational teams to map real workflows, exception paths, approvals, escalation rules, and human-in-the-loop controls. \n Design and build customer-specific AI agent solutions, including orchestration logic, prompt architecture, retrieval flows, workflow rules, and decision logic. \n Implement integrations with customer data sources, APIs, SaaS platforms, CRMs, ERPs, and enterprise knowledge systems so agents can perform real work end to end. \n Develop evaluation methods, guardrails, and acceptance criteria that measure agent usefulness, reliability, safety, task success, and production readiness. \n Run iterative testing, failure analysis, and performance tuning to improve quality, groundedness, latency, cost, and operational effectiveness. \n Prepare solutions for production by addressing access controls, observability, rollout sequencing, exception handling, fallback behavior, and support readiness. \n Lead deployment activities through initial go-live and first-shift stabilization, including rapid issue resolution, workflow adjustments, and customer-facing hypercare. \n Document reusable implementation patterns, operational runbooks, known failure modes, and recommended next improvements to support scale and repeatability. \n Feed field learnings back into Product, Engineering, and transformation teams so future deployments become faster, safer, and more repeatable. \n Detailed solution scoping after deal alignment. \n Customer-specific implementation and agent behavior design. \n Technical integration across enterprise systems and data sources. \n Evaluation, iterative quality improvement, and production hardening. \n Go-live readiness and first-shift production stabilization. \n Executive value framing before opportunity qualification. \n Broad transformation-roadmap design across multiple business units. \n Portfolio-level governance program management. \n Long-term managed-service ownership after the initial deployment phase, unless the service model explicitly extends the role. \n \n Skills you'll bring \n \n Experience in a high-impact, customer-facing technical role such as Forward Deployed Engineering, Solutions Architecture, Technical Consulting, Deployment Engineering, or AI","salary_min":112400,"salary_max":154400,"location":"Anywhere, US","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["agents","embeddings","llm","fine-tuning"],"apply_url":"https://job-boards.greenhouse.io/dialpad/jobs/8734067002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-20T19:03:38Z","expires_at":"2026-09-28T13:52:16.089486Z","created_at":"2026-08-25T19:52:34.272555Z","updated_at":"2026-08-29T13:52:16.257728Z","company_name":"Dialpad","company_slug":"dialpad","company_logo_url":"https://www.google.com/s2/favicons?domain=dialpad.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/42dee226-8fe7-4865-9781-15de96ca3cf0"},{"id":"e8a54bc4-6999-4b3f-bc0e-8b19dbf267a8","company_id":"31ae48bc-c938-4c26-a348-0bf3c089a446","title":"Solution Specialist, Data Services","slug":"solution-specialist-data-services-3a781df1","description":"CoreWeave is The Essential Cloud for AI™. Built for pioneers by pioneers, CoreWeave delivers a platform of technology, tools, and teams that enables innovators to build and scale AI with confidence. Trusted by leading AI labs, startups, and global enterprises, CoreWeave combines superior infrastructure performance with deep technical expertise to accelerate breakthroughs and turn compute into capability. Founded in 2017, CoreWeave became a publicly traded company (Nasdaq: CRWV) in March 2025. Learn more at  www.coreweave.com . \n What You'll Do: \n CoreWeave is constantly launching new services that change what customers can build on AI infrastructure, and the data layer is one of its most important new frontiers. As a Solution Specialist for Data Services, you are the person who opens that frontier. You identify new market opportunities where data architecture, mobility, and pipeline design unlock GPU adoption, and you drive the initial adoption of CoreWeave's newest data capabilities with the earliest customers across new industries. You turn what you learn in the field into direct input on the product roadmap, and you make the broader sales and solution architecture organization fluent in the value these new services create.\n About the role: \n As a Solution Specialist for Data Services, you operate at the leading edge of CoreWeave's go-to-market motion. Your job is not to run an established playbook; it is to create one. You take newly launched data services (high-throughput data movement, plus support for the databases, indexes, and data structures behind AI training, high-concurrency inference, and agentic workloads) into new accounts and new industries, prove their value with the first wave of customers, and establish the repeatable patterns that sales and solution architects use to scale adoption. Along the way you are the field's voice into engineering, translating what early customers need into the priorities that shape CoreWeave's data and storage roadmap.\n In this role, you will:\n \n Own the commercial and technical strategy for net new customer wins in data infrastructure, where storage architecture, data mobility, and pipeline design are the primary buying triggers.\n Drive new business opportunities where data migration complexity, egress costs, or multi-cloud sprawl are the barrier to GPU adoption at scale.\n Translate customer requirements around data lakes, vector databases, and high-speed storage tiers into specific product feedback that shapes CoreWeave's storage roadmap.\n Develop deal structures, technical playbooks, and benchmark narratives that help sales and SA teams accelerate storage-heavy opportunities.\n Engage directly with enterprise buyers as the authoritative voice on data gravity, multi-cloud networking, and the total cost of moving workloads to CoreWeave.\n Design the commercial framework for multi-petabyte data pipeline deals, including egress cost modeling and GPU utilization commitments, to support large enterprise closings.\n Partner with capacity and infrastructure teams to maintain a competitive edge on storage efficiency, performance, and security across active and prospective customer deployments.\n \n Who You Are: \n \n 10+ years of experience in distributed systems, storage engineering, or data architecture, with a track record of applying that expertise to drive customer outcomes and revenue.\n 5+ years working with multi-cloud networking and data transfer protocols (S3, rsync, WAN optimization) in a customer-facing or deal-shaping capacity.\n Deep working knowledge of storage technologies including NVMe-over-Fabric, POSIX filesystems, and object storage, with the ability to translate that into commercial differentiation.\n Experience deploying and tuning large-scale database clusters (SQL, NoSQL, or Vector) and positioning that capability against customer migration and modernization requirements.\n Strong understanding of BGP, peering, and high-speed data interconnects as they relate to data gravity, egress cost modeling, and enterprise deal structure.\n Familiarity with Kubernetes-native storage orchestration (CSI drivers, persistent volumes) and how it impacts workload portability and platform stickiness.\n \n Preferred: \n \n Experience driving new business or shaping product strategy in industries with high-density compute and data needs, such as Financial Services, Biotech and Life Sciences, or Media and Entertainment.\n Prior background in technical sales, solution consulting, or product management supporting large-scale enterprise data infrastructure decisions.\n Deep understanding of multi-cloud networking architecture and secure data egress and ingress strategies, particularly where compliance and data residency requirements are active deal variables.\n Advanced degree in Computer Science or Engineering, or equivalent experience with a demonstrated ability to operate at the intersection of technical architecture and commercial strategy.\n \n Wondering if you're a good fit? \n W","salary_min":207000,"salary_max":275000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["embeddings","agents","distributed-systems","data-pipeline"],"apply_url":"https://coreweave.com/careers/job?4692600006\u0026board=coreweave\u0026gh_jid=4692600006","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-11T12:15:28Z","expires_at":"2026-09-28T13:35:46.71692Z","created_at":"2026-08-25T18:27:34.788526Z","updated_at":"2026-08-29T13:35:46.870796Z","company_name":"CoreWeave","company_slug":"coreweave","company_logo_url":"https://www.google.com/s2/favicons?domain=coreweave.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e8a54bc4-6999-4b3f-bc0e-8b19dbf267a8"},{"id":"f89646a2-035d-42e4-a101-17b62b4dbb93","company_id":"d8e15a46-b80d-4228-8e7b-34f00357f377","title":"RVP - AI Natives","slug":"rvp-ai-natives-aaf7116d","description":"Elastic, the Search AI Company, enables everyone to find the answers they need in real time, using all their data, at scale — unleashing the potential of businesses and people. The Elastic Search AI Platform, used by more than 50% of the Fortune 500, brings together the precision of search and the intelligence of AI to enable everyone to accelerate the results that matter. By taking advantage of all structured and unstructured data — securing and protecting private information more effectively — Elastic’s complete, cloud-based solutions for search, security, and observability help organizations deliver on the promise of AI.\n What Is The Role: \n \n Elastic is seeking a visionary RVP - AI Natives to lead, scale, and accelerate the growth of our specialized AI Native business unit. In this strategic executive role, you will lead a high-performing team responsible for a dual motion: selling Elastic’s enterprise Search, vector search, and generative AI platform directly to digital-native AI companies (e.g., OpenAI, Anthropic, Perplexity, Cohere), and co-building/co-selling strategic sell-with partnerships with these ecosystems. If you are an accomplished software sales leader with a proven track record of scaling high-performing enterprise teams, navigating complex partner ecosystems, and possessing a deep passion for AI infrastructure, we want you to shape the future of AI Search with us. \n \n Location: West of Texas \n What You Will Be Doing: \n \n \n Lead and Coach Teams: Manage, mentor, and coach a team of specialized Account Executives and Strategic Alliance Managers to successfully sell into AI-native organizations and execute high-impact sell-with motions. Actively foster an environment of teamwork, transparency, creativity, and continuous improvement while traveling regularly to provide hands-on executive support. \n \n Drive GTM \u0026 Sell-With Strategy: Build, execute, and own a dual-track GTM strategy: direct enterprise expansion into AI-native companies and strategic sell-with co-sell motions with major AI foundation model providers and platforms. Formulate account coverage, incentive alignment, pipeline generation programs, and customer segmentation tailored to this hyper-growth market segment. \n \n Quota Achievement \u0026 Operational Excellence: Consistently meet or exceed revenue and co-sell targets. Lead by example using rigorous pipeline management, structured forecasting, and deal execution frameworks. Travel regularly to engage directly in deal structuring, co-sell strategy, and executive closures. \n \n Engage C-Suite and Partner Ecosystems: Actively engage in strategic deal cycles to establish trusted-advisor relationships at the CxO, Founder, and VP level within top-tier AI companies. Build strategic, long-term alliances with partner management across product, business development, and go-to-market teams. \n \n Cross-Functional Collaboration: Partner closely with Elastic's global executive leadership , Product, Engineering, Marketing, and Solutions Architecture teams. Provide real-time market telemetry from leading AI innovators to influence Elastic's AI roadmap , while ensuring seamless joint PoC executions and strategic co-marketing initiatives. \n \n What You Bring: \n \n \n SaaS \u0026 Enterprise Sales Leadership : Proven track record leading high-performing software sales teams, with a documented history of quota overachievement in dynamic, high-growth, or strategic alliance environments. \n \n AI \u0026 Search Domain Fluency: Deep understanding of the modern AI tech stack, including vector databases, hybrid search infrastructure, LLMs, retrieval-augmented generation (RAG), and generative AI platforms. \n \n Ecosystem \u0026 Sell-With Expertise: Demonstrated experience building strategic co-sell or sell-with partnerships alongside major cloud, AI, or SaaS ecosystem leaders. \n \n Operational Discipline: Solid analytical capability and data-driven decision-making. Expertise in applying structured methodologies (e.g., MEDDPICC) to complex direct and joint sales cycles. \n \n Entrepreneurial Mindset: The resilience , agility, and initiative-taking attitude required to pioneer a hyper-growth, rapidly evolving vertical and build new market playbooks from scratch. \n \n Bonus Points: \n \n \n Prior experience selling directly to or partnering closely with premier AI foundation model companies (e.g., Anthropic, OpenAI, Perplexity). \n \n Familiarity with open-source software, developer-centric infrastructure GTM strategies, and product-led growth (PLG) dynamics. \n \n #LI-AM2 \n  \n Compensation for this role is in the form of base salary plus a variable component, that together comprise the On-Target Earnings (OTE).   On-Target Earnings (OTE) are based on a 60/40 pay mix (base salary / target variable).   \n The typical starting OTE range for new hires in this role is listed below.  This range represents the lowest to highest OTE we reasonably and in good faith believe we would pay for this role at the time of this posting.  We may ul","salary_min":283200,"salary_max":447900,"location":"United States","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","search","generative-ai","rag","embeddings"],"apply_url":"https://jobs.elastic.co/jobs?gh_jid=8114222\u0026gh_jid=8114222","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-07T15:21:22Z","expires_at":"2026-09-28T13:39:53.894705Z","created_at":"2026-08-25T18:29:01.987196Z","updated_at":"2026-08-29T13:39:54.048472Z","company_name":"Elastic","company_slug":"elastic","company_logo_url":"https://www.google.com/s2/favicons?domain=www.elastic.co\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f89646a2-035d-42e4-a101-17b62b4dbb93"},{"id":"0302e795-5f0c-4232-aac6-3f4d9c1340fb","company_id":"fb64b18b-041a-43de-886d-f506d1ab94a4","title":"Staff AI Platform Engineer, Infrastructure Services","slug":"staff-ai-platform-engineer-infrastructure-services-4e30eaaf","description":"Our Purpose \n At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here.\n About Us \n SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters.\n Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity.\n What Are We Looking For? \n We’re looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.\n As a Staff AI Platform Engineer, Infrastructure Services, you will be tasked with taking ownership of our AI Gateway infrastructure (built on Kong AI Gateway), the system that authenticates, routes, rate-limits, and monitors AI coding assistant traffic org-wide, while also being fluent enough across our broader platform stack to design solutions that span the two. This is a high-autonomy, high-scope role: you will set technical direction for AI infrastructure, drive incident response and reliability work, and partner closely with the engineers who own our CI/CD, GitOps, and artifact systems rather than working in isolation from them.\n What Will You Do?\n Primary responsibilities include:\n \n Work on the AI Gateway platform: architect, harden, and scale our Kong AI Gateway deployment (Konnect Hybrid on KCP/EKS), including auth (Okta/OIDC), consumer tiers and budgets, rate limiting, semantic caching, and observability.\n Lead reliability and incident response: drive root-cause analysis and remediation for gateway issues (timeouts, latency, capacity, failover) and build the monitoring/alerting needed to catch them before users do.\n Design across the platform, not just the gateway: work fluently with our CI/CD (Jenkins, JPAAS), GitOps and Kubernetes deployment tooling (ArgoCD across dev/gov/prod), artifact management (Artifactory/Xray), GitHub Enterprise administration, and GitHub Actions runner fleet, so that AI infrastructure decisions account for how the rest of the platform actually works.\n Evaluate and roll out AI developer tooling: run structured pilots and adoption efforts for tools like AI-assisted PR review (Qodo) and engineering metrics platforms (LinearB), and make clear build-vs-buy recommendations.\n Set technical direction and mentor: define architecture and standards for AI infrastructure, review designs across the team, and raise the bar for other engineers working in this space.\n Partner cross-functionally: work directly with security, DevEx, and product engineering teams consuming the gateway to translate their needs into platform capabilities.\n Host and serve local models: stand up and operate self-hosted/open-weight model serving infrastructure (e.g. vLLM, NVIDIA Triton/NIM, TGI, Ollama) for workloads where routing to an external provider isn't the right fit, including GPU capacity planning, autoscaling, and cost/performance tuning.\n Support the broader model lifecycle: help build LLMOps practices such as model versioning, evaluation, and safe rollout, plus supporting infrastructure for retrieval-augmented generation (vector stores, embedding pipelines) as use cases mature.\n Track usage and cost: build observability into token usage, latency, and spend across both API-based and self-hosted models so the business can see what AI infrastructure actually costs.\n \n What Skills and Knowledge Will You Bring?\n Ideal candidates will have:\n \n 8 or more years of experience in platform, infrastructure, or DevOps engineering, with a track record of owning systems end-to-end in production.\n Hands-on experience with API gateway technologies (Kong, Envoy, Apigee, or similar); direct experience with AI/LLM gateway patterns (rate limiting, semantic caching, prompt/response observability) is a strong plus.\n Strong Kubernetes and GitOps experience (ArgoCD or comparable), and","salary_min":156000,"salary_max":215000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["embeddings","mlops","api-design","security","llm","rag","gpu","fine-tuning"],"apply_url":"https://www.sentinelone.com/jobs/?gh_jid=7823203003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-06T14:00:48Z","expires_at":"2026-09-28T13:50:56.085004Z","created_at":"2026-08-25T18:33:46.389887Z","updated_at":"2026-08-29T13:50:56.250274Z","company_name":"SentinelOne","company_slug":"sentinelone","company_logo_url":"https://www.google.com/s2/favicons?domain=sentinelone.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/0302e795-5f0c-4232-aac6-3f4d9c1340fb"},{"id":"9941177a-20bc-4609-805c-b67d8a59d3a8","company_id":"fb64b18b-041a-43de-886d-f506d1ab94a4","title":"Senior AI Platform Engineer, Infrastructure Services","slug":"senior-ai-platform-engineer-infrastructure-services-d9d4ca58","description":"Our Purpose \n At SentinelOne, we are driven by a clear purpose: to give the advantage to those who secure our future. As AI reshapes how organizations build, operate, and innovate, the responsibility to protect them becomes more critical than ever. When you join SentinelOne, your work helps protect global enterprises, critical infrastructure, and the technologies shaping tomorrow. If you are motivated by meaningful challenges and want your impact to be real, measurable, and global, you will find purpose here.\n About Us \n SentinelOne is a company at the intersection of AI and security, pioneering a new operating model for cybersecurity. Our AI-native platform unifies protection across endpoint, cloud, identity, data, and AI systems to deliver autonomous detection and response with clarity and speed. By combining real-time analytics, intelligent automation, and a unified data foundation, we reduce noise, simplify complexity, and empower security teams to focus on what truly matters.\n Our teams are builders, problem-solvers, and innovators committed to shaping the future of security. If you are excited to solve hard problems alongside talented, mission-driven people, we invite you to help us build a safer future for humanity.\n What Are We Looking For? \n We’re looking for people who are relentlessly curious and committed to continuous learning. AI is reshaping every function across our business, and we enable every team member, regardless of role or level, to build fluency in AI tools and concepts. Those who thrive here actively seek out new solutions, experiment thoughtfully, and apply what they learn to drive better, faster, smarter outcomes.\n As a Senior AI Platform Engineer, Infrastructure Services, you will be tasked with taking ownership of our AI Gateway infrastructure (built on Kong AI Gateway), the system that authenticates, routes, rate-limits, and monitors AI coding assistant traffic org-wide, while also being fluent enough across our broader platform stack to design solutions that span the two. This is a high-autonomy, high-scope role: you will set technical direction for AI infrastructure, drive incident response and reliability work, and partner closely with the engineers who own our CI/CD, GitOps, and artifact systems rather than working in isolation from them.\n What Will You Do?\n Primary responsibilities include:\n \n Work on the AI Gateway platform: architect, harden, and scale our Kong AI Gateway deployment (Konnect Hybrid on KCP/EKS), including auth (Okta/OIDC), consumer tiers and budgets, rate limiting, semantic caching, and observability.\n Lead reliability and incident response: drive root-cause analysis and remediation for gateway issues (timeouts, latency, capacity, failover) and build the monitoring/alerting needed to catch them before users do.\n Design across the platform, not just the gateway: work fluently with our CI/CD (Jenkins, JPAAS), GitOps and Kubernetes deployment tooling (ArgoCD across dev/gov/prod), artifact management (Artifactory/Xray), GitHub Enterprise administration, and GitHub Actions runner fleet, so that AI infrastructure decisions account for how the rest of the platform actually works.\n Evaluate and roll out AI developer tooling: run structured pilots and adoption efforts for tools like AI-assisted PR review (Qodo) and engineering metrics platforms (LinearB), and make clear build-vs-buy recommendations.\n Set technical direction and mentor: define architecture and standards for AI infrastructure, review designs across the team, and raise the bar for other engineers working in this space.\n Partner cross-functionally: work directly with security, DevEx, and product engineering teams consuming the gateway to translate their needs into platform capabilities.\n Host and serve local models: stand up and operate self-hosted/open-weight model serving infrastructure (e.g. vLLM, NVIDIA Triton/NIM, TGI, Ollama) for workloads where routing to an external provider isn't the right fit, including GPU capacity planning, autoscaling, and cost/performance tuning.\n Support the broader model lifecycle: help build LLMOps practices such as model versioning, evaluation, and safe rollout, plus supporting infrastructure for retrieval-augmented generation (vector stores, embedding pipelines) as use cases mature.\n Track usage and cost: build observability into token usage, latency, and spend across both API-based and self-hosted models so the business can see what AI infrastructure actually costs.\n \n What Skills and Knowledge Will You Bring?\n Ideal candidates will have:\n \n 5 or more years of experience in platform, infrastructure, or DevOps engineering, with a track record of owning systems end-to-end in production.\n Hands-on experience with API gateway technologies (Kong, Envoy, Apigee, or similar); direct experience with AI/LLM gateway patterns (rate limiting, semantic caching, prompt/response observability) is a strong plus.\n Strong Kubernetes and GitOps experience (ArgoCD or comparable), an","salary_min":132000,"salary_max":182000,"location":"Remote (US)","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["code-generation","security","llm","fine-tuning","gpu","mlops","embeddings","api-design"],"apply_url":"https://www.sentinelone.com/jobs/?gh_jid=7823236003","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-06T14:00:30Z","expires_at":"2026-09-28T13:50:53.931227Z","created_at":"2026-08-25T18:33:46.305318Z","updated_at":"2026-08-29T13:50:54.18506Z","company_name":"SentinelOne","company_slug":"sentinelone","company_logo_url":"https://www.google.com/s2/favicons?domain=sentinelone.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9941177a-20bc-4609-805c-b67d8a59d3a8"},{"id":"7491aebd-52aa-416c-b202-c306792dbf2a","company_id":"9a024fe2-b507-4b09-9fd0-f31ed05626e4","title":"AI Agent Engineer, Client Facing","slug":"ai-agent-engineer-client-facing-9de11aa4","description":"About Us \n Observe.AI is the AI Agents platform for customer experience, designed to help organizations deliver faster, smarter, and more efficient customer service at scale. The platform enables businesses to deploy specialized AI Agents that autonomously execute work across the full CX lifecycle—from handling customer conversations to supporting frontline teams and optimizing operations.\n Each AI Agent is purpose-built for a specific role, equipped to understand context, make decisions, take action, and continuously improve outcomes. This allows organizations to increase resolution speed, elevate service quality, and reduce operational costs while empowering your frontline team to focus on higher-value work.\n Built on a CX-native foundation, Observe.AI helps leading brands like DoorDash, Affordable Care, Signify Health, and Verida improve customer satisfaction, boost agent productivity, and deliver consistent, scalable performance across every customer interaction.\n Why Join Us \n We’re looking for an AI Agent Engineer to lead the charge in building and deploying enterprise-grade Voice, Chat AI agents and AI Copilot. This role is hands-on, customer-facing, and pivotal in bringing AI solutions to life - from design and integration to deployment and optimization.\n You’ll own the end-to-end lifecycle of AI Agents: building, integrating, testing, demoing to clients, deploying into production, and tuning performance.\n What You’ll Be Doing \n \n Build \u0026 Deploy Agents : Own the implementation of AI Agents including prompt design, workflow configuration, integrations, telephony setup, and evaluation frameworks.\n Client Engagement: Act as the primary technical partner for customers—lead regular demos, communicate progress, gather feedback, and guide solutions from concept to production.\n Systems Integration: Configure and connect systems using APIs—handling authentication, data mapping, error handling, and integrations with CRMs, knowledge bases, and other enterprise tools.\n Telephony Integration: Set up SIP/CCaaS/PSTN routing, pass metadata, configure fallbacks, and troubleshoot call quality.\n Prompt Design \u0026 Optimization: Write and refine prompts for LLM-driven agents, monitor performance, test iteratively, and ensure agents meet automation and containment targets.\n Strategic Partner: Translate customer requirements into actionable solutions; work consultatively to unblock challenges in security, connectivity, or knowledge ingestion.\n Cross Functional Collaboration: Collaborate with product/engineering teams to escalate platform gaps and resolve deep technical fixes and platformization, while independently driving leading client implementations.\n \n What You’ll Bring To The Role \n \n Bachelor’s degree in Computer Science, Engineering, or a related technical field\n 3+ years in conversational AI, solution engineering, system integration, or delivering AI/LLM-based applications in customer environments, software engineering, or system integration with hands-on delivery of AI/LLM-based solutions.\n Strong ability to communicate and  lead customer-facing discussions - from deep technical troubleshooting to weekly project demos. Ability to explain complex technical concepts to non-technical audiences. \n Must have strong hands-on skills in prompt design, workflow building and API integration (SIP, Twilio, Amazon Connect, etc.).\n Familiarity with LLMs (GPT, Claude, Gemini), vector DBs, and orchestration frameworks (LangChain, LlamaIndex, etc.).\n Working knowledge of retrieval-augmented generation (RAG) concepts, implementation patterns and performance optimization.\n Programming experience in Python, JavaScript, or similar for scripting and integrations\n Strong problem-solving mindset: ability to find workarounds, unblock integrations, and adapt to customer-specific ecosystems. \n Experience with integration tools and Integration Platform-as-a-Service (iPaaS) providers, such as n8n, Zapier, or similar platforms and proficiency in API integrations and data flow management is a plus.\n Familiarity with telephony or voice systems (SIP, CCaaS, PSTN) is a plus. \n \n Why You’ll Love It Here   \n \n Competitive compensation including equity: Market-aligned base pay, performance incentives, and meaningful equity ownership\n Excellent medical, dental, and vision insurance options: Comprehensive medical, dental and vision benefits for employees and eligible dependents\n Flexible Paid Time Off: Our unlimited, flexible PTO policy empowers you to take the time you need to recharge, maintain balance, and perform at your best.\n Additional Time to Recharge: 10 company holidays, an annual company-wide Winter Break, and paid parental leave to fully support life outside of work.\n 401(k) plan: Long-term financial planning support with tax-advantaged retirement savings\n Quarterly Lifestyle Spending Account: Flexible quarterly stipend to support wellness, learning and professional development, and personal growth\n Monthly Mobile + I","salary_min":108000,"salary_max":170000,"location":"Redwood City, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"mid","tags":["embeddings","agents","rag","code-generation","cloud","llm","generative-ai"],"apply_url":"https://www.observe.ai/position?gh_jid=5365898008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-03T20:09:07Z","expires_at":"2026-09-28T13:36:14.865576Z","created_at":"2026-08-25T18:27:44.982684Z","updated_at":"2026-08-29T13:36:15.022222Z","company_name":"Observe AI","company_slug":"observe-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=observe.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7491aebd-52aa-416c-b202-c306792dbf2a"},{"id":"e8500f29-6e93-4660-aff6-2889b44125cd","company_id":"b4787255-dacd-444b-8e44-bb9971ec1f36","title":"Principal Cloud Architect","slug":"principal-cloud-architect-14336128","description":"ZoomInfo is where careers accelerate. We move fast, think boldly, and empower you to do the best work of your life. You’ll be surrounded by teammates who care deeply, challenge each other, and celebrate wins. With tools that amplify your impact and a culture that backs your ambition, you won’t just contribute. You’ll make things happen–fast.\n What You'll Do \n \n Prototype and Hand Off: Design platform patterns end-to-end—build reference implementations, document the rationale, and partner with implementation teams to roll them out. Stay hands-on through proof-of-concept and initial enablement, writing reference implementations and opening PRs to jumpstart team adoption.\n Participate in Architecture Review: Bring a consistent, documented rubric to weekly architecture reviews so teams get reliable guidance. Expand our standards library and Architecture Decision Records (ADRs).\n Own a Domain Specialty: Provide architectural stewardship in one of our focus areas:\n \n \n Cloud Infrastructure Architecture: Own the architecture for our cloud runtime, networking, service mesh, container platforms, and overall infrastructure scalability, resilience, and security.\n Data Architecture: Own event streaming/messaging, database technology strategy, pipeline patterns, warehouse, and lakehouse strategies.\n \n \n Define Technology Lifecycle: Evaluate emerging technologies through structured POCs, drive standards for onboarding and phase-out, and lead evaluations of vendor changes and consolidation opportunities. Partner with FinOps on cost optimization in your depth area, including emerging AI/model infrastructure spend (e.g., evaluating open-weight models as a lower-cost alternative to hosted APIs).\n Enable R\u0026D Teams: Host design reviews and workshops. Serve as a technical consultant to engineering teams making complex infrastructure choices. Make patterns consumable and self-service so teams don't reinvent the wheel.\n Shape Multi-Year Strategy: Contribute to the multi-year platform direction—developer experience, delivery pipelines, and AI-augmented architecture review tooling (e.g., MCP servers, LLM-based rubric evaluation)—in partnership with platform engineering teams.\n \n What We're Looking For \n \n Broad Infrastructure Architecture Experience: Proven track record of setting technical direction across large-scale systems many teams depend on—cloud, networking, data, or delivery. Ability to defend architectural choices against real production workloads.\n Multi-Cloud \u0026 Kubernetes Fluency: Production experience with GCP and/or AWS, paired with solid understanding of trade-offs. Practical experience with Kubernetes (GKE or equivalent) as the runtime foundation for modern workloads.\n Infrastructure as Code: Strong proficiency in Terraform, GitOps workflows, and designing/reviewing reusable modules that other teams depend on.\n Depth in At Least One Domain (Nice to Have More): \n \n \n Cloud Infrastructure: Cloud-native networking (AWS transit patterns, GCP shared VPCs, Private Service Connect, VPC peering); Kubernetes/container orchestration (GKE or equivalent) and service mesh (Istio) and mTLS; designing for scalability, resilience, and cost efficiency; ensuring infrastructure and network security.\n Data Architecture: Messaging platforms (Kafka/Confluent, Pub/Sub); database technology fluency across SQL (PostgreSQL, Cloud SQL), NoSQL (MongoDB), columnar analytics (Snowflake, BigQuery), and search (Solr, Elasticsearch); pipeline design (Dataflow, Cloud Composer, MSK, Kinesis); open table formats (Apache Iceberg).\n \n \n Development \u0026 Operational Depth: Ability to dive into code to prove out patterns and evaluate system behavior under load (incidents, on-call impact, capacity, rollout blast radius). Comfortable shipping working prototypes rather than relying solely on high-level diagrams.\n Influence \u0026 Leadership: Strong technical leadership, writing, and presentation skills. Track record of driving standards adoption across engineering organizations without formal managerial authority—through documented rationale, prototypes, workshops, and review processes.\n Technology Evaluation: Demonstrated ability to run rigorous technology evaluations—separating vendor pitch from architectural fit, running POCs, and producing actionable recommendations for engineering leaders.\n AI Infrastructure Fluency: Working knowledge of the infrastructure demands of AI/ML workloads (model serving, vector databases, inference cost and latency trade-offs); able to weigh in on where AI fits into the platform’s technical roadmap.\n \n Bonus Points \n \n Depth in both Cloud Infrastructure and Data Infrastructure domains.\n Experience with GCP organization-level policies, folder structure, and IAM inheritance design.\n Confluent Platform knowledge beyond core Kafka (Schema Registry, Kafka Connect, ksqlDB).\n Experience running or participating in an Architecture Review Council or equivalent governance body.\n Hands-on experience building or applying AI","salary_min":157500,"salary_max":247500,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"principal","tags":["llm","embeddings","mlops","cloud","search","infrastructure"],"apply_url":"https://www.zoominfo.com/careers?gh_jid=8626991002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-08-03T17:51:01Z","expires_at":"2026-09-28T13:50:37.74549Z","created_at":"2026-08-25T18:33:34.912582Z","updated_at":"2026-08-29T13:50:37.922155Z","company_name":"ZoomInfo","company_slug":"zoominfo","company_logo_url":"https://www.google.com/s2/favicons?domain=zoominfo.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/e8500f29-6e93-4660-aff6-2889b44125cd"},{"id":"16742cc9-3f79-4c53-b3e1-18f73c4aeccb","company_id":"a0000000-0000-0000-0000-000000000003","title":"Staff Frontier Agents Engineer (Applied AI)","slug":"staff-frontier-agents-engineer-applied-ai-942edc28","description":"About Scale AI \n Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems.\n Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale.\n The Opportunity \n Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges.\n As a  Staff Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software.\n Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company.\n If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in.\n What You'll Build \n Frontier AI Systems \n \n Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use.\n Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data, and deterministic software into reliable production workflows.\n Engineer customer intelligence layers, retrieval pipelines, memory systems, and knowledge representations that allow agents to reason over large, heterogeneous enterprise data.\n Develop multi-agent systems that coordinate reasoning, planning, tool execution, and human oversight.\n Translate frontier AI research into production systems by rapidly evaluating new models, prompting techniques, reasoning paradigms, and agent architectures.\n \n Experimentation \u0026 Evaluation \n \n Own the full experimentation lifecycle, from hypothesis generation to production rollout.\n Design rigorous evaluation frameworks using offline benchmarks, online A/B experiments, golden datasets, regression suites, LLM-as-a-Judge, and human evaluation.\n Run controlled experiments and ablation studies to understand the contribution of different models, prompts, retrieval strategies, reasoning techniques, memory systems, and agent architectures.\n Continuously evaluate newly released frontier models and determine where they meaningfully improve quality, latency, reliability, or cost.\n Develop confidence estimation, reflection, and continuous learning systems that improve agents over time using real-world feedback.\n Measure success through business outcomes, not benchmark scores.\n \n Production AI Engineering \n \n Build production-quality AI systems with a strong emphasis on reliability, observability, latency, safety, and cost.\n Design agent guardrails, fallback strategies, tracing, monitoring, and evaluation pipelines that enable safe deployment in high-stakes environments.\n Collaborate with infrastructure engineers to deploy AI systems securely within enterprise cloud environments.\n Build human-in-the-loop workflows that effectively combine AI automation with expert oversight.\n \n Customer Innovation \n \n Partner directly with enterprise customers to understand their business, data, and operational challenges.\n Translate ambiguous customer problems into production AI architectures.\n Rapidly prototype new ideas, validate them with customers, and evolve successful solutions into scalable production systems.\n Identify reusable patterns that become core capabilities across many enterprise deployments.\n \n What Makes This Role Different \n You'll work across the full lifecycle of modern AI systems:\n \n Designing reasoning and agent architectures\n Building retrieval, memory, and customer intelligence systems\n Developing predictive models that work alongside LLMs\n Running experiments and ablation studies\n Shipping production systems into enterprise environments\n Measuring business impact through online experimentation\n Continuously improving agents using real-world feedback\n \n We believe the fastest way to grow as an Frontier Agents engineer is to solve many different AI problems, not the same problem repeatedly. You'll work across diverse industries, datasets, model architectures, and agentic systems, rapi","salary_min":252000,"salary_max":315000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["code-generation","embeddings","healthcare","llm","reinforcement-learning","agents","search","generative-ai"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4720487005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-31T23:28:42Z","expires_at":"2026-09-28T13:31:45.968677Z","created_at":"2026-08-25T18:26:38.229526Z","updated_at":"2026-08-29T13:31:46.117077Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/16742cc9-3f79-4c53-b3e1-18f73c4aeccb"},{"id":"6d5ddd81-23a3-4b87-bf78-9309ceb45e12","company_id":"a0000000-0000-0000-0000-000000000003","title":"Senior Frontier Agents Engineer (Applied AI)","slug":"senior-frontier-agents-engineer-applied-ai-cc91553b","description":"About Scale AI \n Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems.\n Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale.\n The Opportunity \n Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges.\n As a Senior Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software.\n Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company.\n If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in.\n What You'll Build \n Frontier AI Systems \n \n Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use.\n Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data, and deterministic software into reliable production workflows.\n Engineer customer intelligence layers, retrieval pipelines, memory systems, and knowledge representations that allow agents to reason over large, heterogeneous enterprise data.\n Develop multi-agent systems that coordinate reasoning, planning, tool execution, and human oversight.\n Translate frontier AI research into production systems by rapidly evaluating new models, prompting techniques, reasoning paradigms, and agent architectures.\n \n Experimentation \u0026 Evaluation \n \n Own the full experimentation lifecycle, from hypothesis generation to production rollout.\n Design rigorous evaluation frameworks using offline benchmarks, online A/B experiments, golden datasets, regression suites, LLM-as-a-Judge, and human evaluation.\n Run controlled experiments and ablation studies to understand the contribution of different models, prompts, retrieval strategies, reasoning techniques, memory systems, and agent architectures.\n Continuously evaluate newly released frontier models and determine where they meaningfully improve quality, latency, reliability, or cost.\n Develop confidence estimation, reflection, and continuous learning systems that improve agents over time using real-world feedback.\n Measure success through business outcomes, not benchmark scores.\n \n Production AI Engineering \n \n Build production-quality AI systems with a strong emphasis on reliability, observability, latency, safety, and cost.\n Design agent guardrails, fallback strategies, tracing, monitoring, and evaluation pipelines that enable safe deployment in high-stakes environments.\n Collaborate with infrastructure engineers to deploy AI systems securely within enterprise cloud environments.\n Build human-in-the-loop workflows that effectively combine AI automation with expert oversight.\n \n Customer Innovation \n \n Partner directly with enterprise customers to understand their business, data, and operational challenges.\n Translate ambiguous customer problems into production AI architectures.\n Rapidly prototype new ideas, validate them with customers, and evolve successful solutions into scalable production systems.\n Identify reusable patterns that become core capabilities across many enterprise deployments.\n \n What Makes This Role Different \n You'll work across the full lifecycle of modern AI systems:\n \n Designing reasoning and agent architectures\n Building retrieval, memory, and customer intelligence systems\n Developing predictive models that work alongside LLMs\n Running experiments and ablation studies\n Shipping production systems into enterprise environments\n Measuring business impact through online experimentation\n Continuously improving agents using real-world feedback\n \n We believe the fastest way to grow as an Frontier Agents engineer is to solve many different AI problems, not the same problem repeatedly. You'll work across diverse industries, datasets, model architectures, and agentic systems, rapid","salary_min":216000,"salary_max":270000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["healthcare","fine-tuning","code-generation","search","embeddings","agents","generative-ai","reinforcement-learning"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4720478005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-31T23:28:08Z","expires_at":"2026-09-28T13:31:42.480641Z","created_at":"2026-08-25T18:26:38.056015Z","updated_at":"2026-08-29T13:31:42.650341Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6d5ddd81-23a3-4b87-bf78-9309ceb45e12"},{"id":"acff52c0-3353-4844-9f9e-fc62961a4eae","company_id":"a0000000-0000-0000-0000-000000000003","title":"Frontier Agents Engineer (Applied AI)","slug":"frontier-agents-engineer-applied-ai-96a49576","description":"About Scale AI \n Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications. We partner with the world's leading enterprises and government organizations to accelerate their AI transformation through frontier AI systems that solve real business problems.\n Every day, we work with organizations across finance, healthcare, manufacturing, media and telecommunications to build production AI agents that automate complex workflows, help humans, reason over enterprise knowledge, and operate safely at scale.\n The Opportunity \n Applied AI is moving faster than ever. New foundation models, reasoning techniques, agent architectures, and research papers emerge every week. Yet building AI systems that reliably solve real-world problems remains one of the hardest engineering challenges.\n As a Frontier Agent Engineer (Applied AI) , you'll bridge the gap between cutting-edge AI research and production deployment. You'll work directly with enterprise customers to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software.\n Unlike traditional ML roles that focus on a single model or product, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases. You may build a multi-agent research system and then participate in designing a customer intelligence platform, a healthcare copilot, or an autonomous workflow for a Fortune 100 company.\n If you enjoy reading new AI papers, experimenting with the latest models, and shipping production systems that create measurable business impact, you'll fit right in.\n What You'll Build \n Frontier AI Systems \n \n Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use.\n Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data, and deterministic software into reliable production workflows.\n Engineer customer intelligence layers, retrieval pipelines, memory systems, and knowledge representations that allow agents to reason over large, heterogeneous enterprise data.\n Develop multi-agent systems that coordinate reasoning, planning, tool execution, and human oversight.\n Translate frontier AI research into production systems by rapidly evaluating new models, prompting techniques, reasoning paradigms, and agent architectures.\n \n Experimentation \u0026 Evaluation \n \n Own the full experimentation lifecycle, from hypothesis generation to production rollout.\n Design rigorous evaluation frameworks using offline benchmarks, online A/B experiments, golden datasets, regression suites, LLM-as-a-Judge, and human evaluation.\n Run controlled experiments and ablation studies to understand the contribution of different models, prompts, retrieval strategies, reasoning techniques, memory systems, and agent architectures.\n Continuously evaluate newly released frontier models and determine where they meaningfully improve quality, latency, reliability, or cost.\n Develop confidence estimation, reflection, and continuous learning systems that improve agents over time using real-world feedback.\n Measure success through business outcomes, not benchmark scores.\n \n Production AI Engineering \n \n Build production-quality AI systems with a strong emphasis on reliability, observability, latency, safety, and cost.\n Design agent guardrails, fallback strategies, tracing, monitoring, and evaluation pipelines that enable safe deployment in high-stakes environments.\n Collaborate with infrastructure engineers to deploy AI systems securely within enterprise cloud environments.\n Build human-in-the-loop workflows that effectively combine AI automation with expert oversight.\n \n Customer Innovation \n \n Partner directly with enterprise customers to understand their business, data, and operational challenges.\n Translate ambiguous customer problems into production AI architectures.\n Rapidly prototype new ideas, validate them with customers, and evolve successful solutions into scalable production systems.\n Identify reusable patterns that become core capabilities across many enterprise deployments.\n \n What Makes This Role Different \n You'll work across the full lifecycle of modern AI systems:\n \n Designing reasoning and agent architectures\n Building retrieval, memory, and customer intelligence systems\n Developing predictive models that work alongside LLMs\n Running experiments and ablation studies\n Shipping production systems into enterprise environments\n Measuring business impact through online experimentation\n Continuously improving agents using real-world feedback\n \n We believe the fastest way to grow as an Frontier Agents engineer is to solve many different AI problems, not the same problem repeatedly. You'll work across diverse industries, datasets, model architectures, and agentic systems, rapidly deve","salary_min":180000,"salary_max":225000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","code-generation","reinforcement-learning","fine-tuning","embeddings","search","healthcare","agents"],"apply_url":"https://job-boards.greenhouse.io/scaleai/jobs/4720573005","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-31T23:25:12Z","expires_at":"2026-09-28T13:31:37.661478Z","created_at":"2026-08-25T18:26:37.839456Z","updated_at":"2026-08-29T13:31:37.81041Z","company_name":"Scale AI","company_slug":"scale-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=scale.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/acff52c0-3353-4844-9f9e-fc62961a4eae"},{"id":"d9e635dd-b7f4-4656-a232-09416838529c","company_id":"9d70a126-16ff-4f5c-9f36-2133735865d3","title":"Software Engineer - Computer Vision","slug":"software-engineer-computer-vision-40522ac4","description":"Who We Are \n Verkada is transforming how organizations protect their people and places with an integrated, privacy-sensitive AI-powered platform that includes solutions for video security, access control, air quality sensors, alarms, intercoms, and visitor management. \n We’ve got serious momentum in the market: more than 30,000 customers (including 100+ of the Fortune 500), a $5.8B valuation , more than $1 billion in annualized bookings, and backing from CapitalG, Sequoia Capital, General Catalyst, Felicis Ventures, Next47 and more. Physical AI is one of the most consequential technology shifts of our time, and Verkada is at the center of it.\n You can look at all kinds of communities to see our platform’s impact in the world. It's the retailer that uses our agentic AI to deter theft before it happens. The warehouse that uses AI-powered alerts to make sure its team is protected on the floor with proper PPE. The school that’s alerted to a threat in real-time and triggers a lockdown in seconds, not minutes. We’re rapidly scaling this impact: today, more than 2 million Verkada devices are deployed across 170+ countries. \n About the Role \n At the forefront of innovation, the Computer Vision team develops the artificial intelligence and machine learning models that power Verkada's advanced analytics. Their responsibilities include creating and refining algorithms for features such as people and vehicle detection, license plate recognition, and other intelligent video analysis tools. Recent projects for this role include:\n \n Implementing and deploying a binary classifier using TensorFlow for detecting the binary states across millions of cameras\n Detecting unusual object addition/removal in a scene\n Detecting and counting object and people frequencies\n Training text image embedding models and vision language models\n Training license plate recognition models and implementing LPR on the edge\n Training facial recognition models and implementing real-time facial recognition\n \n What You'll Do \n \n C++ - writing clean, modular, C++ code\n Traditional computer vision algorithms\n Training deep learning networks using PyTorch, TensorFlow, Keras, or similar\n Data structures and architecture\n Must be willing and able to work onsite five days per week\n \n What You Bring \n \n Bachelor's Degree in Computer Science, preferably with research experience \n 1-3 years of industry software engineering experience\n 1+ years of work or research experience with current neural net frameworks\n Mastery of at least one practical programming language\n Experience working in an agile team software development environment\n \n US Employee Benefits \n Verkada is committed to fostering a workplace environment that prioritizes the holistic health and wellbeing of our employees and their families by offering comprehensive wellness perks, benefits, and resources. Our benefits and perks programs include, but are not limited to:\n \n Healthcare programs that can be tailored to meet the personal health and financial well-being needs - Premiums are 100% covered for the employee under at least one plan and 80% for family premiums under all plans\n Nationwide medical, vision and dental coverage\n Health Saving Account (HSA) with annual employer contributions and Flexible Spending Account (FSA) with tax saving options\n Expanded mental health support\n Paid parental leave policy \u0026 fertility benefits\n Time off to relax and recharge through our paid holidays, firmwide extended holidays, flexible PTO and personal sick time\n Professional development stipend\n Fertility Stipend\n Wellness/fitness benefits\n Healthy lunches provided daily\n Commuter benefits\n \n Additional Information \n \n We do sponsor and take over sponsorship of employment visas for this role. If we make you an offer, we will make every reasonable effort to get you a visa.\n Annual Pay Range \n At Verkada, we want to attract and retain the best employees, and compensate them in a way that appropriately and fairly values their individual contribution to the company. With that in mind, we carefully consider a number of factors to determine the appropriate starting pay for an employee, including their primary work location and an assessment of a candidate's skills and experience, as well as market demands and internal parity. A Verkada employee may be eligible for additional forms of compensation, depending on their role, including sales incentives, discretionary bonuses, and/or equity in the company in the form of restricted stock units (RSUs)\n Below is the annual on-target earnings (OTE) range for full-time employees for this position, comprised of base compensation and commissions (if applicable).\n Estimated Annual Pay Range\n $180,000 — $300,000 USD \n Verkada Is An Equal Opportunity Employer \n As an equal opportunity employer, Verkada is committed to providing employment opportunities to all individuals. All applicants for positions at Verkada will be treated without regard to race, color, ethnicity, r","salary_min":180000,"salary_max":300000,"location":"San Mateo, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["pytorch","tensorflow","deep-learning","embeddings","healthcare","computer-vision","agents"],"apply_url":"https://job-boards.greenhouse.io/verkada/jobs/5195995007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-27T17:40:21Z","expires_at":"2026-09-28T13:40:45.697768Z","created_at":"2026-07-28T14:10:00.958176Z","updated_at":"2026-08-29T13:40:45.851881Z","company_name":"Verkada","company_slug":"verkada","company_logo_url":"https://www.google.com/s2/favicons?domain=verkada.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/d9e635dd-b7f4-4656-a232-09416838529c"},{"id":"756b530d-4528-4497-9a2f-77fe8156d8e4","company_id":"01b03876-5b01-47ab-82b9-696293e861b9","title":"Sr. Software Engineer II, AI Platform","slug":"sr-software-engineer-ii-ai-platform-5dec0454","description":"Who we are \n Samsara (NYSE: IOT) is the pioneer of the Connected Operations™ Cloud, which is a platform that enables organizations that depend on physical operations to harness Internet of Things (IoT) data to develop actionable insights and improve their operations. At Samsara, we are helping improve the safety, efficiency and sustainability of the physical operations that power our global economy. Representing more than 40% of global GDP, these industries are the infrastructure of our planet, including agriculture, construction, field services, transportation, and manufacturing — and we are excited to help digitally transform their operations at scale. \n Working at Samsara means you’ll help define the future of physical operations and be on a team that’s shaping an exciting array of product solutions, including Video-Based Safety, Vehicle Telematics, Apps and Driver Workflows, and Equipment Monitoring. As part of a recently public company, you’ll have the autonomy and support to make an impact as we build for the long term. \n About the role: \n Samsara’s Revenue Operations AI \u0026 Data Team is building the future of how we go to market — with intelligence, personalization, and speed. We’re a high-impact team of builders, scientists, and strategists focused on transforming sales operations through AI. Our mission is to help sellers reach the right customer at the right time with the right message — and to put everything they need at their fingertips, whether that’s data from Salesforce, context from a past call, or content that wins deals.\n As a Senior Software Engineer, AI Platform, you’ll lead the design and development of core platform capabilities that power Samsara’s next generation of AI-driven experiences. You’ll focus on building scalable, reliable systems that enable multi-step AI workflows, model execution, and integrations across products, rather than individual features. This role sits at the intersection of distributed systems and applied AI, where correctness, extensibility, and operational excellence matter as much as speed.\n You’ll partner closely with AI engineers, backend engineers, and cross-functional teams to shape shared execution patterns, define platform contracts, and evolve the foundations that support S+Engine and future AI use cases. You’ll be empowered to make architectural decisions, move fast on early iterations, and help turn emerging AI capabilities into a durable, production-grade platform that other teams can build on with confidence.\n This is a remote position open to candidates residing in the US except the San Francisco Bay Metro Area, NYC Metro Area, and Washington, D.C. Metro Area. \n You should apply if: \n \n You want to impact the industries that run our world: Your efforts will result in real-world impact—helping to keep the lights on, get food into grocery stores, reduce emissions, and most importantly, ensure workers return home safely.\n You are the architect of your own career: If you put in the work, this role won’t be your last at Samsara. We set up our employees for success and have built a culture that encourages rapid career development, countless opportunities to experiment and master your craft in a hyper growth environment.\n You’re energized by our opportunity: The vision we have to digitize large sectors of the global economy requires your full focus and best efforts to bring forth creative, ambitious ideas for our customers.\n You want to be with the best: At Samsara, we win together, celebrate together and support each other. You will be surrounded by a high-calibre team that will encourage you to do your best. \n \n In this role, you will:  \n \n Build and evolve core AI platform capabilities that enable teams to develop, run, and scale GenAI-powered applications across Samsara.\n Design and implement shared execution patterns, APIs, and services that support multi-step AI workflows and system integrations.\n Develop reliable, extensible backend systems that power AI-driven experiences used across the sales funnel and beyond.\n Work hands-on across the stack, from backend services and execution infrastructure to integration with AI models and tooling.\n Collaborate closely with AI engineers, data scientists, product partners, and sales operators to turn emerging AI use cases into production-ready platform capabilities.\n \n Minimum requirements for the role: \n \n 6+ years of professional software engineering experience (excluding internships/contract roles) , with a strong emphasis on building and operating large-scale, production backend or platform systems.\n Hands-on experience building and operating GenAI-powered systems in production , including integration with large language models (LLMs) or similar AI services.\n Experience designing or implementing GenAI workflows such as prompt orchestration, tool execution, routing, or multi-step reasoning pipelines.\n Proven experience designing and implementing distributed systems that ","salary_min":130900,"salary_max":198000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","agents","distributed-systems","embeddings","generative-ai"],"apply_url":"https://www.samsara.com/company/careers/roles/8050373?gh_jid=8050373","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-24T22:28:46Z","expires_at":"2026-09-28T13:34:46.836295Z","created_at":"2026-07-25T14:04:19.041603Z","updated_at":"2026-08-29T13:34:46.987178Z","company_name":"Samsara","company_slug":"samsara","company_logo_url":"https://www.google.com/s2/favicons?domain=www.samsara.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/756b530d-4528-4497-9a2f-77fe8156d8e4"},{"id":"9dc0505f-b9bb-460a-bedb-cd7310931d7a","company_id":"ed18bbda-3537-4b44-9295-c7b575fce0ff","title":"Sr AI Architect - Conversational AI","slug":"sr-ai-architect-conversational-ai-93078a27","description":"Who we are  \n At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to  hundreds of thousands of businesses  and empower millions of developers worldwide to craft personalized customer experiences.\n Our dedication to remote-first work , and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands. . \n Hiring and how we work \n We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions! \n Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings.  . \n See yourself at Twilio \n Join the team as Twilio’s next Sr AI Architect - Conversation AI.\n About the job \n This position is critical to leveraging Twilio’s massive data ecosystem and unmatched communication scale to build our customer facing AI capabilities, such as Twilio Conversational Memory, Enterprise Knowledge, Behavioral Data Intelligence and many more to power the future of our customer engagement platform.\n As a Sr. AI Architect for Twilio Platform, you will also influence the design and evolution of our company-wide ML/AI Ops foundation. You will set the long-term technical vision, establish architectural guardrails, and ensure strict adherence to responsible AI principles. You will drive cross-organizational initiatives, solve complex technical challenges, and elevate the technical standards across all of Twilio. Transitioning AI/ML concepts from cutting-edge research to resilient, compliant, and cost-effective production systems will be your core mission.\n As a Sr AI Architect, you will lead the company as the Distinguished Engineer and AI Contextual Engineering SME, serving as the guiding authority to our Architects, driving company-wide impact, and steering Twilio's overarching technical direction for conversational AI. In this pivotal leadership role, you will also influence the design and evolution of our company-wide ML/AI Ops foundation. You will set the long-term technical vision, establish architectural guardrails, and ensure strict adherence to responsible AI principles. By driving cross-organizational initiatives and solving complex technical challenges, you will elevate the technical standards across all of Twilio. Transitioning AI/ML concepts from cutting-edge research to resilient, compliant, and cost-effective production systems will be your core mission.\n Responsibilities \n In this role, you’ll:\n \n Define and drive a long-term AI/ML architectural vision that aligns with Twilio’s business goals, specifically focusing on how data and memory power the next generation of customer engagement.\n Own the strategic roadmap for Twilio’s ML/AI Ops platform and tooling, ensuring a unified approach to model development, deployment, and lifecycle management across all platform capabilities.\n Evaluate and implement modern LLM architectures, RAG systems, MCP/tooling frameworks, and inference optimization techniques.\n Lead architecture for agentic AI systems including orchestration, reasoning, tool usage, and contextual grounding.\n Stay current with rapidly evolving advancements in LLMs, agent frameworks, reasoning systems, and AI infrastructure.\n Transition seamlessly from high-level strategic communication with executives to deep-dive code reviews and pair programming with engineers. \n Partner closely with Product Management to turn a roadmap into a sequence of technical milestones, ensuring that technical investments always map to customer value.\n Have a 'player-coach' mentality, and contribute hands-on technical expertise while providing strategic direction and mentorship to the team.\n \n Qualifications  \n Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!\n Required: \n \n 15+ years of experience in software engineering, with at least 6+ years specifically focused on building and scaling production-grade ML systems at a platform level.\n Extensive experience with ML Ops and LLM Ops patterns, including designing and implementing rigorous evaluation metrics, automated retraining loops, and monitoring for non-deterministic AI features at scale.\n Deep expertise in the design, architecture, and deployment of production-grade ML/AI systems, including deep knowledge of transformer models, LLM orchestration, embedding models, ","salary_min":324480,"salary_max":405600,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"senior","tags":["mlops","healthcare","llm","payments","agents","rag","fine-tuning","embeddings"],"apply_url":"https://job-boards.greenhouse.io/twilio/jobs/7926891","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-24T22:14:38Z","expires_at":"2026-09-28T13:40:24.989006Z","created_at":"2026-07-25T14:09:34.937099Z","updated_at":"2026-08-29T13:40:25.140609Z","company_name":"Twilio","company_slug":"twilio","company_logo_url":"https://www.google.com/s2/favicons?domain=twilio.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/9dc0505f-b9bb-460a-bedb-cd7310931d7a"}],"page":1,"per_page":20,"total":324,"total_is_exact":true,"total_pages":17}