{"access":{"advertiser_pricing_url":"https://aidevboard.com/pricing","catalog_url":"https://aidevboard.com/api/v1/catalog","description":"Public read endpoints are open and free. API keys are optional for stable agent identity and keyed hourly throttling.","docs_url":"https://aidevboard.com/docs","mode":"open","register_url":"https://aidevboard.com/api/v1/register"},"degraded":false,"estimated":false,"has_next":true,"jobs":[{"id":"fd4226af-9faa-4819-8327-113cce284a3e","company_id":"a355eb2f-63c3-4c0a-803d-bc2d8312b6d8","title":"Software Engineer, Delivery / CD","slug":"software-engineer-delivery-cd-ac48f409","description":"About the Role\n\nThe Engineering Acceleration Delivery / Continuous Deployment team builds and operates the systems that safely ship OpenAI’s infrastructure and product code to production.\n\nWe own the deployment platform, release pipelines, and rollout safety mechanisms that allow engineers across OpenAI to deploy changes rapidly while minimizing operational risk. Our mission is to make production deployments fast, safe, and increasingly autonomous.\n\nThis role sits at the intersection of developer productivity, distributed systems reliability, and large-scale infrastructure orchestration.\n\n\n\nIn This Role, You Will\n\n - Design and build continuous deployment infrastructure that safely rolls out changes across dozens of Kubernetes clusters and global regions.\n\n - Develop systems for progressive delivery, including canary releases, staged rollouts, and automated rollback.\n\n - Improve engineering velocity by reducing friction in the release pipeline and automating manual operational workflows.\n\n - Work with product and infrastructure teams to ensure their services are deployable, observable, and resilient at scale.\n\n - Implement and evolve deployment methodologies such as GitOps, infrastructure-as-code, and progressive delivery patterns.\n\n - Build systems that automatically evaluate deployment health using metrics, logs, traces, and alerts to detect regressions and trigger safe rollbacks.\n\n - Build systems that support agent-assisted or autonomous deployment workflows using modern AI tooling.\n   \n   \n\nTechnologies commonly used in this environment include:\n\n\n\n - Kubernetes for large-scale container orchestration and runtime infrastructure\n\n - Python and FastAPI for internal services\n\n - Terraform for infrastructure as code\n\n - GitOps-based deployment workflows (e.g., ArgoCD, Flux, or similar systems)\n\n - Buildkite for CI orchestration\n   \n\nYou may be a strong fit if you:\n\n - Have worked with Kubernetes-based deployment systems at scale\n\n - Have experience building or operating continuous deployment platforms\n\n - Are familiar with GitOps tooling such as ArgoCD or Flux\n\n - Are excited about building AI-assisted systems and agents that intelligently shepherd software changes from commit to safe production rollout.\n\n - Care deeply about safe production rollouts and minimizing blast radius\n\n - Enjoy building internal platforms that improve developer productivity across the organization\n   \n   \n\nCompensation\n\n$230K – $490K + Offers Equity\n\n\n\n\n\nAbout OpenAI\n\nOpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. \n\nWe are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.\n\nFor additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.\n\nBackground checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.\n\nTo notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241\u0026k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance.\n\nWe are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg\u0026d=57018692298241.\n\nOpenAI Global Applicant Privacy P","salary_min":230000,"salary_max":490000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/openai/e14fc37c-7ae5-4a6b-ba0d-a36860cf9bb2/application","is_featured":true,"is_sticky":false,"status":"active","published_at":"2026-05-04T18:54:22.168Z","expires_at":"2026-08-14T14:01:12.345034Z","created_at":"2026-04-13T09:36:32.989672Z","updated_at":"2026-07-15T14:01:12.47751Z","company_name":"OpenAI","company_slug":"openai","company_logo_url":"https://www.google.com/s2/favicons?domain=openai.com\u0026sz=128","quality_score":85,"url":"https://aidevboard.com/job/fd4226af-9faa-4819-8327-113cce284a3e"},{"id":"53523380-38ba-4300-ab1a-a7402a41ff8f","company_id":"a0000000-0000-0000-0000-000000000001","title":"Staff+ Software Engineer, Capacity Engineering","slug":"staff-software-engineer-capacity-engineering-751b8b8f","description":"About Anthropic \n Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.\n About the Role \n Anthropic manages one of the largest and fastest-growing infrastructure fleets in the industry — spanning multiple accelerator families, cpu families and clouds. The Capacity Engineering team is responsible for making sure all our infrastructure resources are accounted for, well-utilized, and efficiently allocated. We own the data, tooling, and operational systems that let Anthropic plan, measure, and maximize utilization across first-party and third-party compute.\n As an engineer on Capacity Engineering, you will build the production systems that power this work: data pipelines that ingest and normalize telemetry from heterogeneous cloud environments, observability tooling that gives the org real-time visibility into fleet health, and performance instrumentation that measures how efficiently every major workload uses the hardware it’s running on. You will be expected to write production-quality code every day, operate alongside Kubernetes-native infrastructure at meaningful scale, and directly influence decisions around one of Anthropic’s largest areas of spend.\n You’ll collaborate closely with research engineering, infrastructure, inference, and finance teams. The work requires someone who can move between data engineering, systems engineering, and observability with comfort — and who thrives in a high-autonomy, high-ambiguity environment.\n This is a pipeline role feeding four areas. Depending on your background and business priority, you’ll focus primarily in one, but the boundaries are fluid and the problems overlap: \n \n Data platform Pipelines that ingest occupancy and utilization telemetry from Kubernetes clusters, normalize billing and usage across cloud providers, and serve the BigQuery tables the rest of the org queries against. Correctness, completeness, and latency are the job, not a footnote. Consumers range from research engineers to finance to leadership, so it's product work as much as engineering: defining schema contracts, making data discoverable, and figuring out what people actually need.\n Planning Knowing what the fleet has, where it's going, and what's in the way. Making the state of the fleet legible and actionable in real time: cluster health tooling, capacity planning platforms, alerting on occupancy drops and allocation problems, and systemic fixes to scheduling and fragmentation. Kubernetes operations on one side, cross-team coordination on the other.\n Efficiency Measuring and improving how effectively every major workload uses the hardware it runs on. Instrumenting utilization across training, inference, and eval systems, building benchmarking infrastructure, establishing per-config baselines, and working directly with system-owning teams to close the gaps. The metric has to be good enough that the team on the hook for it agrees with the number.\n Attribution and forecasting Connecting what the fleet costs to what the business is doing with it. Reconciling CSP billing exports against vendor telemetry and internal systems with mismatched schemas, attributing spend to the workloads and teams that generate it, and turning inference demand signals and research roadmaps into a defensible compute plan. Efficiency metrics have to survive contact with finance: stripped of pure demand and unit-price effects, reproducible month over month, and legible to a CFO.\n \n Key responsibilities \n \n Build the planning and allocation stack — the tools leadership uses to allocate capacity, teams use to plan against their allocations, and the scheduler enforces. Cross-region and cross-provider placement, guardrails, queueing, occupancy KPIs.\n Drive the efficiency programs: stranding and rightsizing, unused capacity recovery, and job-level utilization across training, inference, and eval. Establish per-config baselines and work with system-owning teams to close the gaps. At this fleet size a single point of utilization is worth eight figures a month.\n Own attribution and forecasting — reconcile billing across ten-plus providers against telemetry and internal systems, attribute spend to the workloads that generate it, and turn demand signals and research roadmaps into a defensible compute plan and supply pipeline.\n Build the data platform underneath all of it: pipelines ingesting occupancy, utilization, and cost from a rapidly diversifying fleet into BigQuery, with real ownership of completeness, latency SLOs, and gap detection. Every new provider is a net-new integration.\n Operate Kubernetes-native systems at scale — collection agents, workload labeling, and the taint/reservation/scheduling behavior that determines what capacity is ac","salary_min":320000,"salary_max":485000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["search","data-pipeline","payments","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/anthropic/jobs/5310731008","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T19:16:22Z","expires_at":"2026-08-14T14:00:36.371223Z","created_at":"2026-07-15T14:00:36.496615Z","updated_at":"2026-07-15T14:00:36.496615Z","company_name":"Anthropic","company_slug":"anthropic","company_logo_url":"https://www.google.com/s2/favicons?domain=anthropic.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/53523380-38ba-4300-ab1a-a7402a41ff8f"},{"id":"c2d1990a-6a3b-4236-9209-26c9f4b3c2e0","company_id":"d3f1a010-47af-48d2-8b4e-a5953078daac","title":"Staff Product Manager, Infrastructure","slug":"staff-product-manager-infrastructure-d7875890","description":"WHY HARVEY\n\nAt Harvey, we’re transforming how legal and professional services operate. By combining frontier agentic AI, an enterprise-grade platform, and deep domain expertise, we’re reshaping how critical knowledge work gets done for decades to come.\n\nThis is a rare chance to help build a generational company at a true inflection point. With 1500+ customers in 60+ countries, strong product-market fit, and world-class investor support, we’re scaling fast and defining a new category in real time. The work is ambitious, the bar is high, and the opportunity for growth — personal, professional, and financial — is unmatched.\n\nOur team moves fast, takes ownership, and is deeply committed to the mission — operating with intensity, staying close to our customers, and pushing each other for excellence. We live by three values: Decisiveness, Simplicity, and Job's Not Finished. We act quickly on clear judgment over perfect information, we believe simplicity is what scales, and we're never satisfied with where we are. If you want to do the best work of your career alongside people who share that drive, we'd love to build with you.\n\nAt Harvey, the future of professional services is being written today — and we’re just getting started.\n\n\n\n\nROLE OVERVIEW\n\nAs a Product Manager on the Core Platform team at Harvey, you'll own the strategy, roadmap, and execution for the infrastructure that powers every user interaction with our global legal AI platform. Harvey serves the world's leading legal teams, processing trillions of tokens and millions of daily requests, and your work will shape how that capability reaches our users.\n\nYou'll operate at the intersection of deep customer need and hard technical constraints, translating the workflows of lawyers and other professionals into product requirements that engineering can build against. You'll balance ambitious, zero-to-one product bets with the operational discipline required to keep a mission-critical platform reliable, scalable, and secure as we expand across products, regions, and customers. Your decisions will directly influence adoption, retention, and the trust that our enterprise customers place in Harvey.\n\n\n\n\nWHAT YOU'LL DO\n\nYou'll partner directly with our Head of Infrastructure to define and drive the product vision and roadmap for a core area of the Harvey platform, aligning it with company strategy and grounding it in evidence from customers (external and internal), data, and the market. You'll work closely with engineering, product, and go-to-market teams to ship high-quality products on a predictable cadence, and you'll own the outcomes those products produce.\n\nDay to day, you will own the entire infrastructure planning, prioritization, and roadmapping. You’ll make and communicate crisp prioritization decisions, balancing new capabilities against reliability, performance, and security. You'll define the metrics that matter for your area — adoption, engagement, quality, and business impact — and hold the team accountable to them. You'll also serve as the connective tissue across functions, ensuring that customer feedback, competitive dynamics, and technical realities all inform the product direction, and you'll raise the product bar across the organization through rigorous specs, reviews, and decision-making. Some projects include architecting multi-region deployment strategies, developing comprehensive observability infrastructure, and more.\n\n\n\n\n\n\n\nWHAT YOU HAVE\n\n - 6+ years of product management experience shipping and scaling software platforms in a production environment, with a track record of measurable impact\n\n - Experience owning complex, technical products end to end, including platform, infrastructure, or AI/ML capabilities\n\n - Strong ability to translate ambiguous problems and deep customer needs into clear strategy, crisp requirements, and prioritized roadmaps\n\n - Fluency working with engineering and design teams on technical trade-offs, and comfort engaging with concepts like distributed systems, APIs, and cloud infrastructure at a level sufficient to make informed decisions\n\n - Excellent analytical skills, with the ability to define metrics and use data to guide decisions\n\n - Outstanding written and verbal communication, and a demonstrated ability to influence and align stakeholders across functions\n\n - A high bar for quality, strong product judgment, and a \"spidey sense\" for where a product experience could break down\n\nNice to Have\n\n - Experience building products for legal, professional-services, or other expert users with demanding accuracy and trust requirements\n\n - Background with AI/ML products, LLM-powered applications, or high-throughput inference systems\n\n - Experience with multi-tenant, enterprise platforms subject to strict security and compliance requirements\n\n - Prior experience partnering closely with infrastructure or platform engineering teams\n\n - A prior career in law or another professional-services field, or e","salary_min":213600,"salary_max":300000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","cloud","llm","agents","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/harvey/d629fa64-599d-435c-b4ef-a925299ddac8/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-14T00:04:08.326Z","expires_at":"2026-08-14T14:02:50.722292Z","created_at":"2026-07-15T14:02:50.87055Z","updated_at":"2026-07-15T14:02:50.87055Z","company_name":"Harvey AI","company_slug":"harvey-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=harvey.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/c2d1990a-6a3b-4236-9209-26c9f4b3c2e0"},{"id":"7275bf2f-408c-49d7-b90d-3a9476dd880f","company_id":"f36ec848-cb19-4b95-a680-6733e58086c0","title":"Product Cybersecurity Engineer","slug":"product-cybersecurity-engineer-168adafd","description":"May Mobility is transforming cities through autonomous technology to create a safer, greener, more accessible world. Based in Ann Arbor, Michigan, May develops and deploys autonomous vehicles (AVs) powered by our innovative Multi-Policy Decision Making (MPDM) technology that literally reimagines the way AVs think. Our vehicles do more than just drive themselves - they provide value to communities, bridge public transit gaps and move people where they need to go safely, easily and with a lot more fun. We’re building the world’s best autonomy system to reimagine transit by minimizing congestion, expanding access and encouraging better land use in order to foster more green, vibrant and livable spaces. Since our founding in 2017, we’ve given more than 500,000 autonomous rides to real people around the globe. And we’re just getting started. We’re hiring people who share our passion for building the future, today, solving real-world problems and seeing the impact of their work. Join us. \n Job Summary \n The Product Cybersecurity Engineer is responsible for ensuring security is embedded throughout the product development lifecycle—from architecture and code to deployment and operations. This role integrates security practices into development workflows, manages vulnerabilities in vehicle and autonomous systems, supports compliance with automotive cybersecurity standards, and serves as a cross-functional security expert bridging cybersecurity, hardware, and product engineering teams.\n Essential Responsibilities \n \n Integrate security practices — threat modeling, architecture reviews into product development workflows from requirements through release.\n Provide early security input on hardware, firmware, and software design decisions, including third-party and supply chain risk considerations.\n Write, review, and validate security requirements across hardware and software domains; enforce secure coding standards and perform security analysis on main compute systems.\n Assist with maintaining Software Bill of Materials (SBOM) and Hardware Bill of Materials (HBOM) using dedicated SBOM tooling to ensure component visibility, vulnerability tracking, and supply chain transparency across products.\n Apply security lenses during safety and functional assessments in collaboration with safety, systems, and software teams.\n Assist in proactive vulnerability patching and support secure update strategies using product security tooling for threat modeling and risk profiling.\n Conduct hazard and threat analyses (TARA/HARA) early in the architecture and development lifecycle.\n Analyze and harden the security architecture of vehicle subsystems and autonomous stacks; define system- and product-level security requirements and ensure validation coverage.\n Assist senior level engineers with Ethernet, in-vehicle networking, and cloud interface configuration, including port security and network segmentation.\n Maintain working knowledge of R155/156, ISO 21434 and UL 4600; support internal audits, risk assessments, and compliance documentation.\n Engage with Auto-ISAC to track emerging threats, attack vectors, and industry best practices.\n Work across teams such as cybersecurity, hardware, and product engineering — providing architectural security design feedback.\n Assist with fostering a security-first culture across the organization through integrated best practices and awareness programs.\n Perform additional responsibilities as directed by your manager.\n \n Skills and Abilities \n Success in this role typically requires the following competencies: \n \n Clear written communication and the ability to align stakeholders on security priorities before executing.\n Excellent attention to detail and a rigorous, systematic approach to security analysis.\n Ability to identify complex security problems across hardware, firmware, and software and devise optimal, innovative solutions that often cross organizational boundaries.\n \n Qualifications and Experience \n Candidates most successful in this role typically hold the following qualifications or comparable knowledge or experience: \n Required \n \n B.S. Degree in Computer Science, Computer Engineering, or an equivalent degree \n Minimum of [1-3] years of experience in a product cyber security or related role\n Experience performing threat modeling and attack surface analysis \n Experience generating and managing Software Bills of Materials (SBOMs) using industry tooling, with working knowledge of SBOM formats such as SPDX and CycloneDX\n Familiarity with vehicle communication networks and protocols across physical and application layers (CAN, LIN, Ethernet, DBCs), embedded systems interaction, and module security technologies.\n Familiarity with security-relevant services in ISO 14229-1 (UDS)\n Experience in TARA and HARA methodologies; experience applying UNECE WP.29, ISO/SAE 21434, and security standards.\n Ability to clearly communicate findings and collaborate with engineering teams to drive t","salary_min":100000,"salary_max":155000,"location":"Remote (US)","workplace":"remote","remote_scope":"restricted","job_type":"full-time","experience_level":"mid","tags":["healthcare","security","autonomous-vehicles","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/maymobility/jobs/8497183002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T19:42:53Z","expires_at":"2026-08-14T14:20:05.536745Z","created_at":"2026-07-15T14:20:05.63743Z","updated_at":"2026-07-15T14:20:05.63743Z","company_name":"May Mobility","company_slug":"may-mobility","company_logo_url":"https://www.google.com/s2/favicons?domain=maymobility.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/7275bf2f-408c-49d7-b90d-3a9476dd880f"},{"id":"394498a7-3e09-4b7d-9dc4-98c2d5cce6a3","company_id":"ccb23d77-c69e-462b-a941-02ce99527e78","title":"Software Engineer I (Data Eng infra)","slug":"software-engineer-i-data-eng-infra-ce880ce9","description":"Who we are \n Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.\n The Aurora Driver  will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.\n  \n At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit  aurora.tech  or follow us on  LinkedIn .\n  \n What we are looking for \n Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. \n We are seeking a talented and experienced Software Engineer to join our data engineering and infrastructure team. In this role, you will be working with our seasoned engineers and contribute to the design, development, and maintenance of our data platform, building the scalable and reliable systems that enable our organization to leverage data for insights and product innovation. You will work on the core data lake and data warehouse ecosystem infrastructure, data pipelines, and tools that process data at massive scale, ensuring it is accessible, high-quality, and secure.\n In this role, you will \n \n Design, build, and maintain robust and scalable data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse.\n Develop and manage data infrastructure components using AWS cloud services and infrastructure-as-code tools like Terraform.\n Collaborate with data scientists, analysts, autonomy engineering teams and product teams to understand their data needs and build solutions that meet their requirements.\n Optimize data processing systems for performance, reliability, and cost-efficiency.\n Implement monitoring, alerting, and logging for data pipelines and infrastructure to ensure operational stability.\n Champion best practices in data governance, data quality, and security.\n \n Required Qualifications \n \n Bachelor’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.\n 1+ years of recent professional experience in software engineering, with a focus on data-related projects.\n Proficiency in at least one programming language commonly used for data engineering (e.g., Python, Go or C++).\n Preliminary experience with big data processing frameworks like Apache Spark, Flink, Kinesis Data Stream, or similar technologies.\n Hands-on experience with cloud platforms (AWS, GCP, or Azure) and their data services (e.g., S3, Redshift, BigQuery, Glue).\n Strong knowledge of SQL and experience working with relational and NoSQL databases.\n Preliminary knowledge of data analytics infrastructure, including data transformation tools such as DBT and visualization frameworks and tools\n Experience with building and managing data pipelines using an orchestrator like Apache Airflow.\n Able to systematically approach open-ended questions to identify pragmatic data solutions that scale\n Able to work effectively in a highly cross-functional, fast-moving and high-stakes environment\n Proven ability to communicate technical, data-driven solutions to both technical and non-technical audiences across stakeholders\n \n Desirable Qualifications  \n \n Experience with data warehousing solutions like Snowflake or data lake architectures.\n Familiarity with modern data stack tools and practices.\n A passion for building elegant, scalable, and maintainable systems.\n Experience using Amazon Web Services (AWS) tools\n \n The base salary wage range for this position is $116K-$174K per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. \n  #LI-SP1 \n Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.\n We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week.\n Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom .\n Our commitment to safety \n At the core of everything we do is our commitment to safety. Building best-in-class self-driving technology will take time, and we believe that each employee at ","salary_min":116000,"salary_max":174000,"location":"Mountain View, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"junior","tags":["cloud","autonomous-vehicles","data-pipeline","infrastructure","data-science"],"apply_url":"https://aurora.tech/jobs/8628066002?gh_jid=8628066002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T13:24:28Z","expires_at":"2026-08-14T14:06:40.709003Z","created_at":"2026-07-15T14:06:40.845277Z","updated_at":"2026-07-15T14:06:40.845277Z","company_name":"Aurora Innovation","company_slug":"aurora-innovation","company_logo_url":"https://www.google.com/s2/favicons?domain=aurora.tech\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/394498a7-3e09-4b7d-9dc4-98c2d5cce6a3"},{"id":"536847ab-380b-4023-a67d-e6f42968d89e","company_id":"ccb23d77-c69e-462b-a941-02ce99527e78","title":"Senior Software Engineer (Data Engineering and Infrastructure)","slug":"senior-software-engineer-data-engineering-and-infrastructure-fbb63209","description":"Who we are \n Aurora’s mission is to deliver the benefits of self-driving technology safely, quickly, and broadly.\n The Aurora Driver  will create a new era in mobility and logistics, one that will bring a safer, more efficient, and more accessible future to everyone.\n  \n At Aurora, you will tackle massively complex problems alongside other passionate, intelligent individuals, growing as an expert while expanding your knowledge. For the latest news from Aurora, visit  aurora.tech  or follow us on  LinkedIn .\n  \n What we are looking for \n Aurora hires talented people with diverse backgrounds who are ready to help build a transportation ecosystem that will make our roads safer, get crucial goods where they need to go, and make mobility more efficient and accessible for all. We are seeking a talented and experienced Software Engineer to join our data engineering and infrastructure team. In this role, you will be a key contributor to the design, development, and maintenance of our data platform, building the scalable and reliable systems that enable our organization to leverage data for insights and product innovation. You will work on the core data lake and data warehouse ecosystem infrastructure, data pipelines, and tools that process data at massive scale, ensuring it is accessible, high-quality, and secure.\n In this role, you will \n \n Design, build, and maintain robust and scalable data pipelines and ETL/ELT processes to ingest, transform, and load data from various sources into our data warehouse.\n Develop and manage data infrastructure components using AWS cloud services and infrastructure-as-code tools like Terraform.\n Collaborate with data scientists, analysts, autonomy engineering teams and product teams to understand their data needs and build solutions that meet their requirements.\n Optimize data processing systems for performance, reliability, and cost-efficiency.\n Implement monitoring, alerting, and logging for data pipelines and infrastructure to ensure operational stability.\n Champion best practices in data governance, data quality, and security.\n Work closely with other senior team members and management to improve the data ecosystem toolings, refine user experience, and continuously polish team roadmap.\n \n Required Qualifications \n \n Master’s degree in Computer Science, Engineering, or a related field, or equivalent practical experience.\n 5+ years of professional experience in software engineering, with a focus on data-related projects.\n Proficiency in at least one programming language commonly used for data engineering (e.g., Python, Go or C++).\n Solid experience with big data processing frameworks like Presto/Trino, EMR, Apache Spark, Flink, Kinesis Data Stream, or similar technologies.\n Hands-on experience with cloud platforms (AWS, GCP, or Azure) and their data services (e.g., S3, Redshift, BigQuery, Glue).\n Strong knowledge of SQL and experience working with relational and NoSQL databases.\n Intermediate knowledge of data analytics infrastructure, including data transformation tools such as DBT and visualization frameworks and tools\n Experience with building and managing data pipelines using an orchestrator like Apache Airflow.\n Able to systematically approach open-ended questions to identify pragmatic data solutions that scale\n Able to work effectively in a highly cross-functional, fast-moving and high-stakes environment\n Proven ability to communicate technical, data-driven solutions to both technical and non-technical audiences across stakeholders\n \n Desirable Qualifications  \n \n Experience with AI toolings, LLM and agentic frameworks\n Experience with data warehousing solutions like Snowflake or data lake architectures.\n Familiarity with modern data stack tools and practices.\n A passion for building elegant, scalable, and maintainable systems.\n Experience using Amazon Web Services (AWS) tools\n \n The base salary range for this position is $146K-$234K per year.  Aurora’s pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, qualifications, relevant education or training, and market conditions. These ranges may be modified in the future. The successful candidate will also be eligible for an annual bonus, equity compensation, and benefits. \n  #LI-SP1 \n Working at Aurora At Aurora, we bring together extraordinarily talented and experienced people united by the strength of our values. We operate with integrity, set outrageous goals, and build a culture where we win together — all without any jerks.\n We believe in-person work increases collaboration, empathy and our ability to lead effectively. As a result, we operate in a hybrid work environment where Aurorans are in office at least 3 days per week.\n Our Careers page provides insight into what it is like to work at Aurora, and you can find all the latest updates in our Newsroom .\n Our c","salary_min":146000,"salary_max":234000,"location":"Pittsburgh, PA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["cloud","agents","autonomous-vehicles","llm","data-pipeline","infrastructure","data-science","data-engineering"],"apply_url":"https://aurora.tech/jobs/8628064002?gh_jid=8628064002","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-13T13:23:27Z","expires_at":"2026-08-14T14:06:40.546103Z","created_at":"2026-07-15T14:06:40.677939Z","updated_at":"2026-07-15T14:06:40.677939Z","company_name":"Aurora Innovation","company_slug":"aurora-innovation","company_logo_url":"https://www.google.com/s2/favicons?domain=aurora.tech\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/536847ab-380b-4023-a67d-e6f42968d89e"},{"id":"e02f64f7-97ca-4df9-8c15-82b1bb16fb2f","company_id":"52f44519-9f93-4eac-ae0b-8be13e385ebe","title":"Backend Infrastructure Engineer","slug":"backend-infrastructure-engineer-03331b6c","description":"BACKEND INFRASTRUCTURE ENGINEER\n\n\n\nYou'll work on the infrastructure that makes Firecrawl fast and reliable against a web that constantly changes and fights back. This is deep systems work: keeping success rates high against sites with aggressive defenses, managing the proxy layer that powers reliable data collection at scale, and pushing throughput and reliability under heavy, spiky load. When Firecrawl \"just works\" on a site that tries hard to stop it, that's this team. You'll own real infrastructure from day one, not tickets in a backlog.\n\n\n\nSalary Range: $200,000–$250,000/year (Range shown is for U.S.-based employees in San Francisco, CA. Compensation outside the U.S. is adjusted fairly based on your country's cost of living.)\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 in backend, networking, or infrastructure engineering\n\nVisa: Must already be authorized to work in the US or our eligible remote-hire regions. 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 147k+ 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 - Build and maintain the infrastructure that powers reliable data collection at scale\n\n - Improve success rates against sites with aggressive defenses\n\n - Own the health, rotation, and cost efficiency of the proxy layer\n\n - Push throughput and reliability under heavy, spiky, real-world load\n\n - Debug hard, intermittent failures across the stack and make them stay fixed\n\n\n\n\nWHAT WE'RE LOOKING FOR\n\n - You've worked on networking, proxies, or high-throughput backend systems\n\n - You're relentless about reliability and comfortable in messy, adversarial problem spaces\n\n - You can own a system end to end and keep it healthy in production\n\n - You move fast and close the loop - you'd rather ship, measure, and iterate than perfect on paper\n\n\n\n\nWHAT WE'RE NOT LOOKING FOR\n\n - Someone who wants clean, well-defined problems only\n\n - Someone who avoids on-call or production ownership\n\n - Someone who needs the environment to be stable to do their best work\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 — $200,000–$250,000/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 recharge\n\n - Parental leave — 12 weeks fully paid, for all parents\n\n - Wellness stipend — $100/month for the gym, therapy, massages, or whatever keeps you human\n\n - Learning \u0026 Development — Expense up to $1,000/year toward anything that helps you grow professionally\n\n - Team offsites — A change of scenery, minus the trust falls\n\n - Sabbatical — 3 paid months off after 4 years, do something fun and new\n\n\n\n\nAVAILABLE TO US-BASED FULL-TIME EMPLOYEES\n\n - Full coverage, no red tape — Medical, dental, and vision (100% for employees, 50% for spouse/kids) — no weird loopholes, just care that works\n\n - Life \u0026 Disability insurance — Employer-paid short-term disability, long-term disability, and life insurance — coverage for life's curveballs\n\n - Supplemental options — Optional accident, critical illness, hospital indemnity, and voluntary life insurance for extra peace of mind\n\n - Doctegrity telehealth — Talk to a doctor from your couch\n\n - 401(k) plan — Retirement might be a ways off, but future-you will thank you\n\n - Pre-tax benefits — Access to FSAs and commuter benefits (US-only) to help your wallet out a bit\n\n - Pet insurance — Because fur babies are family too\n\n\n\n\nAVAILABLE TO SF-BASED EMPLOYEES\n\n - SF HQ perks — Snacks, drinks, team lunches, intense ping pong, and peak startup energy\n\n - E-Bike tran","salary_min":200000,"salary_max":250000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["llm","agents","infrastructure","backend"],"apply_url":"https://jobs.ashbyhq.com/firecrawl/6840bbee-aae5-4846-97a2-ec2e764ee75b/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-12T22:41:44.402Z","expires_at":"2026-08-14T14:17:49.939042Z","created_at":"2026-07-15T14:17:50.121535Z","updated_at":"2026-07-15T14:17:50.121535Z","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/e02f64f7-97ca-4df9-8c15-82b1bb16fb2f"},{"id":"21fc5b88-2cc6-41e7-aabb-4eb32c4e3b24","company_id":"6ea0f41a-b13e-481a-b410-5195f391f939","title":"Staff Platform Engineer, Service Infrastructure","slug":"staff-platform-engineer-service-infrastructure-e2c5b795","description":"About the Role \n Together AI is hiring a Staff Platform Engineer to join the Product Foundations engineering organization and drive its service infrastructure strategy.\n Product Foundations builds and operates Together’s mission-critical product platforms that support all cloud products, including API Platform (non-Inference), web UI Platform, Billing, and customer-facing IAM. These services sit on the critical path for customers and internal systems.\n This is a hands-on Staff role focused on evolving Product Foundations’ core infrastructure strategy from the inside: understanding service team needs, turning repeated infrastructure problems into reusable patterns, and coordinating across platform owners so Product Foundations services are reliable, repeatable, and built on the right company-wide foundations.\n Responsibilities \n \n Own the technical direction for service infrastructure within Product Foundations, including Kubernetes, AWS, Terraform, CDNs, ALBs, DNS, IAM, service networking, and related operational patterns.\n Up-level existing Product Foundations services by improving reliability, operability, deployment safety, infrastructure consistency, and production readiness.\n Partner deeply with API Platform and UI Platform on networking, DNS, CDN, load balancing, delivery, and gateway patterns for critical customer-facing interfaces.\n Work closely with Infrastructure, Networking, and Security teams to bring company-wide platform standards into Product Foundations and contribute PF requirements back into shared frameworks.\n Help drive cross-company infrastructure initiatives that Product Foundations depend on or help maintain, including Terraform CI/CD, Kubernetes networking, zero-trust service communication, policy-as-code, and cross-DC/provider networking.\n Build and evolve reusable service infrastructure primitives, including Helm charts, Terraform modules, GitHub Actions/GitOps workflows, service scaffolding, runbooks, and documentation.\n Establish durable technical standards through design docs, architecture reviews, mentorship, and hands-on implementation that help Together scale services across teams, regions, and cloud environments.\n \n Requirements \n \n 7+ years of professional experience in platform engineering, service infrastructure, SRE, distributed systems, cloud infrastructure, or related roles.\n Deep production experience with Kubernetes, including EKS, Helm, ArgoCD/Argo Rollouts, ingress, autoscaling, secrets, service identity, networking, and progressive delivery.\n Strong Terraform experience, including module design, infrastructure CI/CD, policy enforcement, production applies, and safe self-service workflows.\n Experience operating networking and edge infrastructure such as CDNs, ALBs/NLBs, DNS, TLS, ingress/egress controls, and traffic management.\n Proficiency in one or more programming languages used for infrastructure tooling and automation, such as Go, Python, TypeScript, or similar.\n AWS experience, ideally including EKS, IAM, VPC networking, load balancing, Route 53, CloudFront, ECR, and related service infrastructure.\n Direct experience with observability systems, including metrics, logs, traces, dashboards, alerting, SLOs, and incident response.\n Proven ability to lead cross-functional technical initiatives across product engineering, infrastructure, networking, and security teams.\n Strong written communication skills, with experience producing clear design docs, migration plans, operational guidance, and technical standards.\n Staff-level judgment: you can define ambiguous problems, make pragmatic tradeoffs, influence without authority, and leave both systems and teams better than you found them.\n \n Nice to Have \n \n Experience building internal developer platforms or paved-path service frameworks used by many engineering teams.\n Experience embedding infrastructure best practices into product engineering teams at scale.\n Experience with service mesh or zero-trust infrastructure such as mTLS, SPIFFE/SPIRE, Cilium, Istio, Linkerd, Envoy, or similar.\n Experience with OPA, Gatekeeper, Kyverno, Sentinel, or other policy-as-code systems.\n Experience with multi-region, multi-cluster, hybrid-cloud, or cross-provider service networking.\n Experience with supply-chain security, image signing, SBOMs, vulnerability management, or compliance automation.\n \n About Together AI \n Together AI is a research-driven artificial intelligence company. We believe open and transparent AI systems will drive innovation and create the best outcomes for society, and together we are on a mission to significantly lower the cost of modern AI systems by co-designing software, hardware, algorithms, and models. We have contributed to leading open-source research, models, and datasets to advance the frontier of AI, and our team has been behind technological advancement such as FlashAttention, Hyena, FlexGen, and RedPajama. We invite you to join a passionate group of researchers in our journey in building the nex","salary_min":240000,"salary_max":280000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["cloud","payments","distributed-systems","platform","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/togetherai/jobs/5180690007","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T22:06:31Z","expires_at":"2026-08-14T14:02:21.334902Z","created_at":"2026-07-12T14:01:51.382499Z","updated_at":"2026-07-15T14:02:21.458268Z","company_name":"Together AI","company_slug":"together-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=together.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/21fc5b88-2cc6-41e7-aabb-4eb32c4e3b24"},{"id":"da65e8fc-123b-47b4-a19f-f1b5fde0fc84","company_id":"77beb456-fc80-40a4-b773-f0b17d1ece4c","title":"AI Infrastructure Engineer","slug":"ai-infrastructure-engineer-aabaa04d","description":"ABOUT MESHY\n\nHeadquartered in Silicon Valley, Meshy is the leading 3D generative AI company on a mission to Unleash 3D Creativity by transforming the content creation pipeline. Meshy makes it effortless for both professional artists and hobbyists to create unique 3D assets—turning text and images into stunning 3D models in just minutes. What once took weeks and cost $1,000 now takes just 2 minutes and $1.\n\nOur world-class team of top experts in computer graphics, AI, and art includes alumni from MIT, Stanford, and Berkeley, as well as veterans from Nvidia and Microsoft. Our talent spans the globe, with team members distributed across North America, Asia, and Oceania, fostering a diverse and innovative multi-regional culture focused on solving global 3D challenges. Meshy is trusted by top developers, backed by premiere venture capital firms like Sequoia and GGV, and has successfully raised $52 Million in funding.\n\nMeshy is the market leader, recognized as the No.1 in popularity among 3D AI tools (according to 2024 A16Z Games) and No.1 in website traffic (according to SimilarWeb, with 3 Million monthly visits). The platform boasts over 5 Million users and has generated 40 Million models.\n\nFounder and CEO Yuanming (Ethan) Hu earned his Ph.D. in graphics and AI from MIT, where he developed the acclaimed Taichi GPU programming language (27K stars on GitHub, used by 300+ institutes). His work is highly influential, including an honorable mention for the SIGGRAPH 2022 Outstanding Doctoral Dissertation Award and over 2,700 research citations.\n\n\n\n\n\nABOUT THE ROLE\n\n - This role sits at the intersection of platform engineering, site reliability, and applied ML systems. The function owns the reliability, scalability, and operability of Meshy's AI model serving stack, along with core engineering infrastructure. The team operates a conventional production infrastructure (CI/CD, build systems, deployment, runtime environments) and develops a model-serving platform that connects the models developed by our Research Team to product-facing backend systems. The position is systems-heavy, production-oriented, and focused on turning experimental model artifacts into robust, observable, and cost-efficient services.\n\n\n\n\n\nJOB RESPONSIBILITIES\n\n - Responsible for the design, development, and optimization of core capabilities for the AI inference platform, including key modules such as inference services, task scheduling, service orchestration, elastic scaling, and release governance.\n\n - Participate in the development of CPU/GPU resource management systems to optimize stability, resource utilization, and cost efficiency in scenarios where online inference and training tasks are run on the same cluster.\n\n - Drive the unified management and scheduling of GPU resources, and explore the practical implementation of capabilities such as MIG, MPS, time-sharing, and virtualization in real-world business operations.\n\n - Continuously optimize the throughput, latency, and availability of the inference pipeline, refining engineering quality in complex inference pipelines, multi-model collaboration, and high-concurrency scenarios.\n\n - Focus on R\u0026D efficiency, resource and cost management, online stability, and disaster recovery architecture design to drive the company’s continuous evolution in performance, reliability, and maintainability.\n\n - Explore AI-native infrastructure and automated operations to make infrastructure smarter and more user-friendly, supporting the company’s rapid expansion during its startup phase.\n\n \n\n\nQUALIFICATIONS\n\n - Bachelor’s degree or higher; majors in Computer Science, Software Engineering, Artificial Intelligence, Telecommunications, or related fields are preferred.\n\n - 1 to 3 years of experience in backend development, infrastructure, cloud-native platforms, machine learning platforms, or AI platforms.\n\n - Proficiency in at least one of Go or Python, with solid software engineering skills and a strong commitment to code quality.\n\n - Understanding of fundamental principles in Linux, operating systems, computer networks, and distributed systems; ability to independently identify and resolve complex engineering issues.\n\n - Practical development experience with Kubernetes, Docker, microservices, or distributed systems, with a basic understanding of production system stability.\n\n - Real-world project experience in areas such as model inference, task orchestration, resource scheduling, and service stability—beyond mere conceptual understanding.\n\n - Self-motivated, curious, and a fast learner; willing to take on greater ownership and broader responsibilities in a startup environment, while continuously learning and quickly adopting new technologies.\n\n\nNICE TO HAVE\n\n - Experience with GPU inference platforms, Kubernetes schedulers, Device Plugins, or related platform development.\n\n - Familiarity with frameworks such as Ray and Ray Serve, or experience in developing and optimizing model serving, distributed in","salary_min":175000,"salary_max":300000,"location":"San Francisco, CA","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["generative-ai","agents","microservices","mlops","distributed-systems","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/meshy/e82eca7a-4704-4af3-a84f-94c6fb5e1034/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T21:33:17.539Z","expires_at":"2026-08-14T14:12:17.728298Z","created_at":"2026-04-13T15:01:38.817296Z","updated_at":"2026-07-15T14:12:17.854855Z","company_name":"Meshy","company_slug":"meshy","company_logo_url":"https://www.google.com/s2/favicons?domain=meshy.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/da65e8fc-123b-47b4-a19f-f1b5fde0fc84"},{"id":"6f80d97a-d8d1-487f-935c-a688dee93d62","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Software Engineer, Cloud Infrastructure","slug":"senior-software-engineer-cloud-infrastructure-7a92e8c8","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\n\nABOUT THE TEAM\n\nThe Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.\n\nRead more about the infra team's work here: https://decagon.ai/blog/what-an-air-gapped-ai-deployment-actually-requires\n\n\n\n\nABOUT THE ROLE\n\nDecagon builds agentic AI that resolves customer support conversations end to end, for companies ranging from fast-growing startups to some of the largest financial institutions in the world. Keeping that system fast, reliable, and secure (across our multi-tenant cloud and inside customers' own locked-down environments) is an infrastructure problem, and that's the problem this role owns.\n\nYou'll build the platforms and abstractions our product teams ship on, and you'll architect and operate the deployments that run our agents inside enterprise customer clouds, where security, compliance, and operational rigor matter as much as speed. The work is core infrastructure at heart: reliability, CI/CD, deployment automation, on-call. You'll be joining a team with real infrastructure and momentum already in place, but there's no established playbook for running agentic systems at this scale, so a big part of the job is figuring it out as the technology shifts and usage grows by orders of magnitude.\n\n\n\n\n\nWHAT YOU'LL DO\n\n - Build the platform\n   \n   - Design the development and production platforms that power our products, and the abstractions over cloud infrastructure, Kubernetes, and networking that let engineers ship without becoming infrastructure experts.\n   \n   - Make sure it all scales to the next order of magnitude as usage grows.\n\n - Own enterprise deployments\n   \n   - Take end-to-end ownership of deployment architecture in customer-owned cloud environments (VPC configuration, permissioning, networking, provisioning) and the full lifecycle that follows: setup, upgrades, scaling, and incident support.\n   \n   - Build the runbooks and automation that make it repeatable.\n\n - Keep agentic workloads reliable\n   \n   - Treat monitoring, alerting, and rollback as first-class parts of anything you ship, not afterthoughts.\n   \n   - Own the reliability of the systems our AI agents depend on in production, where latency, availability, and graceful degradation directly shape the customer experience.\n\n - Partner across boundaries\n   \n   - Work directly with customers' platform, security, and DevOps teams to navigate their infrastructure and compliance constraints, and with our Product, Security, Sales, and Customer Success teams to turn customer requirements into concrete deployment plans.\n     \n\n\nYOUR BACKGROUND LOOKS SOMETHING LIKE THIS\n\n - 4+ years building and operating core infrastructure, platform engineering, or infrastructure/DevOps, ideally with some customer-facing deployment experience.\n\n - Deep experience with a major cloud provider (GCP, AWS, or Azure), along with Terraform and Kubernetes at scale.\n\n - Strong grasp of cloud networking fundamentals (VPCs, IAM, DNS, load balancing) and how they surface as real deployment constraints.\n\n - A track record operating production systems reliably: monitoring, on-call, incident response, and reasoning about failure modes up front.\n\n - Comfort navigating ambiguity across a range of stakeholders, from engineers to security and compliance teams, and turning those conversations into actionable plans.\n\n - Clear technical writing and a track record of driving adoption across teams.\n\n - Comfortable in a fast-moving environment with rapid change.\n\n\n\n\nEVEN BETTER IF YOU HAVE\n\n - Experience managing deployments in customer-owned cloud environments, including security reviews, compliance requirements, and change management.\n\n - Experience building internal platforms or paved roads: service templates, self-serve environments, CI/CD pipeline design, dep","salary_min":200000,"salary_max":400000,"location":"New York, NY","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","agents","cloud","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/decagon/4203f138-c427-49b6-8201-4437db28e1de/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T20:53:01.652Z","expires_at":"2026-08-14T14:09:19.030816Z","created_at":"2026-07-12T14:06:49.759609Z","updated_at":"2026-07-15T14:09:19.189688Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/6f80d97a-d8d1-487f-935c-a688dee93d62"},{"id":"17d8babe-c5a5-4343-95c4-5fca23745817","company_id":"776e5e7d-beba-4889-a481-6d9d7c3af325","title":"Senior Software Engineer, Cloud Infrastructure","slug":"senior-software-engineer-cloud-infrastructure-a2c7d597","description":"About Decagon\n\nDecagon is the leading conversational AI platform empowering every brand to deliver concierge customer experiences.\n\nOur technology enables industry-defining enterprises like Avis Budget Group, Block’s Cash App and Square, Chime, Oura Health, and Hunter Douglas to deploy AI agents that power personalized, deeply satisfying interactions across voice, chat, email, SMS, and every other channel.\n\nWe’re building a future where customer experiences are being redefined from support tickets and hold music to faster resolutions, richer conversations, and deeper relationships. We’re proud to be backed by world-class investors who share that vision, including a16z, Accel, Bain Capital Ventures, Coatue, and Index Ventures, along with many others.\n\nWe’re an in-office company, driven by a shared commitment to excellence and velocity. Our values — Just Get It Done, Invent What Customers Want, Winner’s Mindset, and The Polymath Principle — shape how we work and grow as a team.\n\n\n\n\nABOUT THE TEAM\n\nThe Infrastructure team builds and operates the foundations that power Decagon: networking, data, ML serving, developer platform, and real‑time voice. We partner closely with product, data, and ML to deliver high‑scale, low‑latency systems with clear SLOs and great developer ergonomics.\n\nRead more about the infra team's work here: https://decagon.ai/blog/what-an-air-gapped-ai-deployment-actually-requires\n\n\n\n\nABOUT THE ROLE\n\nDecagon builds agentic AI that resolves customer support conversations end to end, for companies ranging from fast-growing startups to some of the largest financial institutions in the world. Keeping that system fast, reliable, and secure (across our multi-tenant cloud and inside customers' own locked-down environments) is an infrastructure problem, and that's the problem this role owns.\n\nYou'll build the platforms and abstractions our product teams ship on, and you'll architect and operate the deployments that run our agents inside enterprise customer clouds, where security, compliance, and operational rigor matter as much as speed. The work is core infrastructure at heart: reliability, CI/CD, deployment automation, on-call. You'll be joining a team with real infrastructure and momentum already in place, but there's no established playbook for running agentic systems at this scale, so a big part of the job is figuring it out as the technology shifts and usage grows by orders of magnitude.\n\n\n\n\nWHAT YOU'LL DO\n\n - Build the platform\n   \n   - Design the development and production platforms that power our products, and the abstractions over cloud infrastructure, Kubernetes, and networking that let engineers ship without becoming infrastructure experts.\n   \n   - Make sure it all scales to the next order of magnitude as usage grows.\n\n - Own enterprise deployments\n   \n   - Take end-to-end ownership of deployment architecture in customer-owned cloud environments (VPC configuration, permissioning, networking, provisioning) and the full lifecycle that follows: setup, upgrades, scaling, and incident support.\n   \n   - Build the runbooks and automation that make it repeatable.\n\n - Keep agentic workloads reliable\n   \n   - Treat monitoring, alerting, and rollback as first-class parts of anything you ship, not afterthoughts.\n   \n   - Own the reliability of the systems our AI agents depend on in production, where latency, availability, and graceful degradation directly shape the customer experience.\n\n - Partner across boundaries\n   \n   - Work directly with customers' platform, security, and DevOps teams to navigate their infrastructure and compliance constraints, and with our Product, Security, Sales, and Customer Success teams to turn customer requirements into concrete deployment plans.\n     \n\n\nYOUR BACKGROUND LOOKS SOMETHING LIKE THIS\n\n - 4+ years building and operating core infrastructure, platform engineering, or infrastructure/DevOps, ideally with some customer-facing deployment experience.\n\n - Deep experience with a major cloud provider (GCP, AWS, or Azure), along with Terraform and Kubernetes at scale.\n\n - Strong grasp of cloud networking fundamentals (VPCs, IAM, DNS, load balancing) and how they surface as real deployment constraints.\n\n - A track record operating production systems reliably: monitoring, on-call, incident response, and reasoning about failure modes up front.\n\n - Comfort navigating ambiguity across a range of stakeholders, from engineers to security and compliance teams, and turning those conversations into actionable plans.\n\n - Clear technical writing and a track record of driving adoption across teams.\n\n - Comfortable in a fast-moving environment with rapid change.\n\n\n\n\nEVEN BETTER IF YOU HAVE\n\n - Experience managing deployments in customer-owned cloud environments, including security reviews, compliance requirements, and change management.\n\n - Experience building internal platforms or paved roads: service templates, self-serve environments, CI/CD pipeline design, depl","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","cloud","distributed-systems","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/decagon/87d6c46a-365c-4d97-98ca-de7e29b6cf72/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-10T20:52:30.112Z","expires_at":"2026-08-14T14:09:18.941296Z","created_at":"2026-07-12T14:06:49.67441Z","updated_at":"2026-07-15T14:09:19.075089Z","company_name":"Decagon","company_slug":"decagon","company_logo_url":"https://www.google.com/s2/favicons?domain=decagon.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/17d8babe-c5a5-4343-95c4-5fca23745817"},{"id":"bc91a0c1-1d1c-4a5e-9fd5-09aa89273d51","company_id":"9bad7e3a-74e6-4dae-87c5-f3e9f0e72bd0","title":"AI Engineer – Enterprise, Data \u0026 AI","slug":"ai-engineer-enterprise-data-ai-03046a5f","description":"Zoox is seeking a highly motivated, hands-on AI Engineer to spearhead the end-to-end development and deployment of our Enterprise Gen AI and LLM initiatives. You will serve as the primary technical driver for establishing guard rails, building AI agents and automated workflows that fundamentally transform operations across Procurement, Supply Chain, Legal, Finance, HR and Marketing. This is an engineering-intensive role for a self-starter who thrives on developing, implementing and scaling production-ready AI systems that add business value by solving complex cross-functional challenges.\n","salary_min":190000,"salary_max":250000,"location":"Foster City, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["agents","generative-ai","llm","infrastructure"],"apply_url":"https://jobs.lever.co/zoox/ba2b9418-e041-43b9-9bb1-b19762a00bd6/apply","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T23:31:54.641Z","expires_at":"2026-08-14T14:07:46.264862Z","created_at":"2026-07-15T14:07:46.41165Z","updated_at":"2026-07-15T14:07:46.41165Z","company_name":"Zoox","company_slug":"zoox","company_logo_url":"https://www.google.com/s2/favicons?domain=zoox.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/bc91a0c1-1d1c-4a5e-9fd5-09aa89273d51"},{"id":"78bb5e81-4dfe-4ed2-af4d-f819687a5629","company_id":"e455f75a-a424-4955-9844-afebe8ea6eb4","title":"Cloud Infrastructure Architect, Okta Federal","slug":"cloud-infrastructure-architect-okta-federal-be26a5b7","description":"Secure Every Identity, from AI to Human Identity is the key to unlocking the potential of AI. Okta secures AI by building the trusted, neutral infrastructure that enables organizations to safely embrace this new era. This work requires a relentless drive to solve complex challenges with real-world stakes. We are looking for builders and owners who operate with speed and urgency and execute with excellence. This is an opportunity to do career-defining work. We're all in on this mission. If you are too, let's talk.\n \n  Technology, Data, and Insights (TDI) is on a mission to accelerate Okta's scale and growth. We bring world-class business acumen and technology expertise to every interaction. We also drive cross-functional collaboration and are focused on delivering measurable business outcomes.\n The TDI Infrastructure Engineering team owns the foundational platforms that power Okta's business — from cloud infrastructure and AI platform delivery to network engineering, developer productivity, observability, and client platforms. We are a team of builders who design and operate at scale, and we are in the middle of a strategic transformation: evolving our cloud practice from a self-service model into a managed, opinionated platform that the entire business can rely on.\n The Cloud Platform Architect Opportunity\n Okta Federal, Inc. is looking for a dedicated Cloud Platform Architect for TDI Infrastructure Engineering — the technical authority for how we design, build, and evolve the cloud infrastructure that underpins our AI platform and the broader workloads running across the business. You will define the architectural standards, patterns, and strategies that the Cloud Platform Engineering team builds to, and you will serve as a key partner to AI, security, and productivity architects as we scale Okta's cloud capabilities to meet increasing business demand.\n This is a hands-on builder role. We are not looking for someone who advises from a distance — we need someone who has shipped cloud infrastructure at scale and brings the credibility and depth to make sound architectural decisions in a fast-moving environment. You will operate at a critical moment: Okta's AI platform is scaling rapidly, our cloud platform team is transforming, and the foundational decisions made now will define the trajectory of our infrastructure for years.\n This role reports directly to the Director of Infrastructure Engineering.\n What You'll Be Doing\n \n Define and own Okta's Cloud Platform architecture — establish reference architectures, design standards, and guardrails that bring consistency, security, and reliability to workloads running across the business\n Lead the architecture for Kubernetes and EKS — design and evolve our cluster strategy, multi-tenancy model, networking topology, and security posture as the platform scales to support AI agent workloads and diverse business unit deployments\n Elevate Okta's AI platform — partner with AI architects and platform engineers to evolve our agent and model-serving infrastructure from its current state to a production-grade, scalable platform capable of supporting broad business adoption\n Drive multi-cloud strategy — build the evaluation framework and decision criteria for when and how Okta leverages AWS, Azure, and Google Cloud; ensure workload placement is intentional and optimized for performance, cost, and capability\n Serve as the technical anchor for the Cloud Platform Engineering team — raise the architectural quality of everything the team designs and builds as we complete the transformation from account vending to a managed platform model\n Partner cross-functionally with AI, security, and productivity architects, product managers, and business unit stakeholders to ensure cloud infrastructure decisions align with Okta's product, compliance, and operational requirements — including support for federal programs and FedRAMP environments\n Partner cross-functionally to design cloud-native solutions that can be effectively adapted for air-gapped, self-hosted environments like US Secret (SIPRNet) and US Top Secret (JWICS).\n Help architect and validate foundational Kubernetes and infrastructure designs within unclassified AWS GovCloud sandboxes. You will ensure these commercial-side designs translate seamlessly when tested against emulators that simulate the strict constraints of air-gapped networks.\n Ensure our commercial cloud platform architecture shares foundational DNA with our highly regulated deployments, aligning with DoD-centric frameworks like the USAF's \"Big Bang\" architecture and utilizing Iron Bank hardened containers where applicable.\n \n What You'll Bring to the Role\n \n 10+ years of hands-on cloud infrastructure experience with deep, demonstrated expertise in one or more major cloud providers (AWS, GCP, or Azure) — including compute, networking, storage, IAM, and managed services at enterprise scale; AWS experience is preferred given our current environmen","salary_min":244000,"salary_max":336000,"location":"Washington, DC","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["fine-tuning","mlops","cloud","agents","data-pipeline","embeddings","infrastructure"],"apply_url":"https://www.okta.com/company/careers/opportunity/8004104?gh_jid=8004104","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T17:52:28Z","expires_at":"2026-08-14T14:11:18.197322Z","created_at":"2026-07-10T14:08:46.130561Z","updated_at":"2026-07-15T14:11:18.324586Z","company_name":"Okta","company_slug":"okta","company_logo_url":"https://www.google.com/s2/favicons?domain=okta.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/78bb5e81-4dfe-4ed2-af4d-f819687a5629"},{"id":"90b670fb-c16e-4406-9cd7-c2e700e6570a","company_id":"c0136eba-1fff-477a-8968-c5435a645cd3","title":"Senior AI Infrastructure Engineer - Model Training","slug":"senior-ai-infrastructure-engineer-model-training-1ae1d299","description":"Kodiak Robotics, Inc. was founded in 2018 and has become a leader in autonomous ground transportation committed to a safer and more efficient future for all. The company has developed an artificial intelligence (AI) powered technology stack purpose-built for commercial trucking and the public sector. The company delivers freight daily for its customers across the southern United States using its autonomous technology. In 2024, Kodiak became the first known company to publicly announce delivering a driverless semi-truck to a customer. Kodiak is also leveraging its commercial self-driving software to develop, test and deploy autonomous capabilities for the U.S. Department of Defense.\n Kodiak's AI is only as good as the speed at which we can train it. Every improvement to our models – from GigaFusionNet to large-scale world models – depends on infrastructure that turns thousands of hours of multimodal driving data into training throughput. We are looking for engineers who make model training fast: streaming massive camera, LiDAR, and radar datasets without stalling a single GPU, sharding data and models efficiently across nodes, and extracting every FLOP from the latest hardware. If you measure your impact in tokens per second and GPU utilization, this role is for you. In this role, you will: \n \n Design high-throughput data loading and streaming systems for multimodal sensor data (camera, LiDAR, radar), including dataset formats, sharding strategies, and prefetching pipelines that keep GPUs saturated \n Build and optimize distributed training infrastructure across multi-node GPU clusters, applying data, tensor, pipeline, and fully sharded (FSDP/ZeRO) parallelism to models that don't fit on a single device \n Maximize utilization of modern accelerators such as NVIDIA B200s through mixed-precision training (BF16/FP8), fused kernels, memory optimization, and communication/computation overlap \n Profile end-to-end training pipelines to find and eliminate bottlenecks across storage, network, CPU preprocessing, and GPU compute \n Develop scalable dataset construction pipelines that convert petabytes of raw driving logs into training-ready, streamable formats \n Partner with ML teams to scale new architectures from prototype to full-cluster training runs efficiently and reliably \n \n What you’ll bring: \n \n BS, MS, or PhD in Computer Science or a related field, and at least 2-3 years of industry experience in ML systems or infrastructure \n Hands-on experience with distributed training frameworks and techniques (PyTorch DDP/FSDP, DeepSpeed, Megatron, NCCL) and a strong grasp of parallelism trade-offs \n Experience building high-performance data pipelines for large-scale training, including streaming dataset formats (WebDataset, MosaicML Streaming/MDS, or similar), sharding, and storage/network-aware loading \n Deep understanding of GPU performance: mixed precision, memory hierarchy, kernel fusion, profiling tools (Nsight, PyTorch Profiler), and interconnects (NVLink, InfiniBand) \n Strong Python skills and proficiency in PyTorch internals; systems-level experience (C++/CUDA/Triton) a plus \n Passion for building the infrastructure that lets AI for the physical world train faster, scale further, and improve continuously \n \n What we offer: \n \n Competitive compensation package including equity and annual bonuses \n Excellent Medical, Dental, and Vision plans through Kaiser Permanente, Cigna, and  MetLife (including a medical plan with infertility benefits) \n MetLife Legal Services, Identity \u0026 Fraud Protection, Hospital Indemnity Insurance, Accident Insurance, \u0026 Critical Illness Insurance \n Flexible PTO, 10 paid holidays, and generous parental leave policies \n Our office is centrally located in Mountain View, CA \n Office perks: dog-friendly, free catered lunch, a fully stocked kitchen, and free EV charging \n Long Term Disability, Short Term Disability, Life Insurance \n Wellbeing Benefits - Headspace through Cigna, Calm through Kaiser, One Medical, Gympass, Spring Health through Cigna, Rula (mental health navigation)  \n Fidelity 401(k) \n Commuter, FSA, Dependent Care FSA, HSA \n Various incentive programs (referral bonuses, patent bonuses, etc.) \n The pay range listed below reflects the base salary  in our SF/Silicon Valley location,  across several internal levels. Actual starting pay will be based on job-related factors including: work location, experience, relevant training, education, skill level and performance during interview. Total compensation at Kodiak includes base pay, equity, bonus and a competitive benefits package\n California Pay Range\n $190,000 — $260,000 USD \n  \n At Kodiak, we strive to build a diverse community working towards our common company goals in a safe and collaborative environment where harassment of any kind is strictly prohibited. Kodiak is committed to equal opportunity employment regardless of race, ethnicity, religion, gender identity, sexual orientation, age, disability, or veteran status,","salary_min":190000,"salary_max":260000,"location":"Mountain View, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["pytorch","robotics","autonomous-vehicles","gpu","data-pipeline","distributed-systems","infrastructure","machine-learning"],"apply_url":"https://job-boards.greenhouse.io/kodiak/jobs/4310775009","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T16:07:51Z","expires_at":"2026-08-14T14:10:22.491332Z","created_at":"2026-07-10T14:08:04.242712Z","updated_at":"2026-07-15T14:10:22.616943Z","company_name":"Kodiak Robotics","company_slug":"kodiak-robotics","company_logo_url":"https://www.google.com/s2/favicons?domain=kodiak.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/90b670fb-c16e-4406-9cd7-c2e700e6570a"},{"id":"a78c1e6e-02a1-4e7c-aa23-10d382bb3863","company_id":"4c0fefc3-173a-4227-a823-4d67d3e70ff0","title":"Senior Engineering Manager, AI Infrastructure","slug":"senior-engineering-manager-ai-infrastructure-8804a5af","description":"Persons in these roles are expected to work from our offices in Seattle. On-site requirements vary based on position and team. If you have questions about on-site work arrangements for this role, please ask your recruiter.\n Our base salary range is $146,880 - $220,320, and in addition we have generous bonus plans to provide a competitive compensation package. \n Who You Are: \n We are seeking a Senior Manager, AI Infrastructure to run the day-to-day operation of the systems that power our research. Reporting to the VP of Engineering, you will own the execution and reliability of our high-performance computing (HPC) environment which includes on-prem GPU clusters and the software orchestration layer that schedules workloads across a hybrid cloud environment. This is a hands-on operational leadership role: your mandate is to keep the platform fast, reliable, and well-utilized, and to deliver against the roadmap set with your PM counterpart.\n Our ideal candidate is a:\n \n Systems Expert: You have a deep, hands-on understanding of the Linux kernel, container runtimes, and distributed systems. You understand the performance implications of InfiniBand topologies and NCCL optimizations.\n Execution-Focused Leader: You plan and deliver against near-term operational goals, keep reliability and researcher velocity high, and turn priorities set with leadership into shipped, dependable systems.\n Pragmatic Operator: You are comfortable making trade-offs between technical elegance and operational necessity. You triage and mitigate immediate risks, and know when to handle something yourself versus escalate.\n \n Who We Are:  \n Ai2 is a non-profit research institute at the forefront of open-source AI development. Unlike industry peers, our goal is to share our findings, data, code, and models with the global scientific community. \n Why Ai2: \n \n Open Science: Your work directly enables the release of open models like OLMo, providing the broader research community with tools they can't get elsewhere.\n Mission-Driven: We prioritize scientific impact over profit margins. This allows us to focus on building the \"right\" infrastructure for long-term research goals.\n Complexity at Scale: You will manage some of the most dense and high-performance compute environments currently in operation.\n \n Your Next Challenge: \n \n Cluster Operations: Manage the availability, performance, and health of our dense on-prem GPU clusters. Coordinate with hardware vendors and internal teams to keep physical infrastructure meeting the demands of frontier model training.\n Orchestration \u0026 Scheduling: Operate and improve Beaker, our internal orchestration platform by optimizing resource allocation and driving high utilization across on-prem assets and elastic cloud resources (AWS/GCP).\n Storage Operations: Execute and continuously improve our storage environment, balancing high-throughput performance for active training against cost-effective durability for petascale research data. Contribute to the longer-term storage roadmap.\n Resource Management: Manage GPU compute allocation against budget. Track utilization, surface the data, and recommend when to burst to the cloud versus investing in on-prem capacity, escalating larger trade-offs as needed.\n User Support \u0026 Velocity: Serve as the technical bridge to our research teams. Ensure infrastructure is an accelerator, not a bottleneck, for a diverse set of research objectives.\n Team Leadership: Manage and grow a team of systems engineers, SREs, and software developers. Set the bar for operational rigor, engineering quality, and a collaborative culture, and keep the team unblocked and delivering.\n \n What You’ll Need: \n \n Experience: 12+ years in infrastructure, systems engineering, or HPC (or an advanced degree with 8+ years), including 2+ years supervising a small engineering team (5+).\n Bachelor's degree in a related field : a relevant advanced degree may substitute for equivalent years of technical work experience.\n GPU/HPC Stack: Direct experience operating large-scale NVIDIA GPU clusters and high-performance networking (InfiniBand/RoCE).\n Orchestration: Strong background in Kubernetes, Slurm, or similar orchestration frameworks, particularly in hybrid-cloud configurations.\n Storage: Hands-on experience with distributed filesystems (e.g., WEKA, Ceph, Lustre) and cloud storage integration at scale.\n Software Development: Proficient in designing and managing SDLC processes including sprint planning and technical design reviews. Proficient in Go or Python.\n \n Physical Demands and Work Environment: \n The physical demands described here are representative of those that must be met by a team member to successfully perform the essential functions of this position. Reasonable accommodations may be made to enable individuals with disabilities to perform the functions.\n \n Must be able to remain in a stationary position for long periods of time. \n The ability to communicate information and ideas so others will unde","salary_min":146880,"salary_max":220320,"location":"Seattle, WA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["distributed-systems","healthcare","gpu","robotics","infrastructure"],"apply_url":"https://job-boards.greenhouse.io/thealleninstitute/jobs/8029564","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-09T00:47:06Z","expires_at":"2026-08-14T14:19:34.338033Z","created_at":"2026-07-09T14:16:58.241171Z","updated_at":"2026-07-15T14:19:34.435381Z","company_name":"Allen Institute for AI","company_slug":"allen-institute-for-ai","company_logo_url":"https://www.google.com/s2/favicons?domain=allenai.org\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/a78c1e6e-02a1-4e7c-aa23-10d382bb3863"},{"id":"92eff494-6559-427b-8a18-9f3ed481a25a","company_id":"2114efab-ea67-411b-bfb8-7899153105f3","title":"Member of Technical Staff, CI/CD Infrastructure","slug":"member-of-technical-staff-cicd-infrastructure-1daba4be","description":"Inferact's mission is to grow vLLM as the world's AI inference engine and accelerate AI progress by making inference efficient and faster. Founded by the creators and core maintainers of vLLM, we sit at the intersection of models and hardware—a position that took years to build.\n\n\n\n\nABOUT THE ROLE\n\nvLLM is growing at a fast pace, and every bit of that growth lands on the CI system. More models, more hardware, more contributors, more ways for things to break. Your job is to advance the CI system so it scales with vLLM’s momentum and unlocks faster development for everyone.\n\nYou’ll get to:\n\n - Maintain and scale the compute infrastructure that powers CI, release, performance benchmark, accuracy evaluation for vLLM project, across a wide range of models and accelerators including H100/H200, (G)B200/300, AMD MI325/355X, TPU, Intel Gaudi, etc..\n\n - Get creative about cutting CI time-to-signal from hours to minutes\n\n - Make sure every corner of vLLM code base is well-tested\n\n - Keep vLLM releases rock-solid\n\n - Build out tooling that helps 3,000+ vLLM contributors move fast\n\n\n\n\nSKILLS AND QUALIFICATIONS\n\nMinimum qualifications:\n\n - Strong experience with Docker, Kubernetes, and containerized build or test environments.\n\n - Built CI/CD pipelines from scratch using GitHub Actions, Buildkite, or similar systems.\n\n - Familiar with CI design patterns and CI techniques: compute orchestration, handling flaky tests, dependency/environment management, caching, remote execution, test target determination, etc, test coverage, and so on.\n\n - Fluent in Python, Bash, Go, or similar for automation and tooling.\n\n - Solid fundamentals of Linux, security, networking, storage, package management,.\n\nBonus points for:\n\n - Setting up infrastructure for ML, inference, CUDA, ROCm, or accelerator-heavy workloads.\n\n - Running Buildkite at scale, including agents, queues, dynamic pipelines, test sharding, caching, and artifact management.\n\n - Operating Kubernetes clusters for CI, batch jobs, test execution, or internal developer infrastructure.\n\n - Managing CI/CD in large open-source project\n\n - Building dashboards, alerts, runbooks, or tooling for CI observability.\n\n\nLOGISTICS\n\n - Location: This role is based in San Francisco, California. Will consider remote in the US for exceptional candidates.\n\n - Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $400,000 USD + equity.\n\n - Visa sponsorship: We sponsor visas on a case-by-case basis.\n\n - Benefits: Inferact offers generous health, dental, and vision benefits as well as 401(k) company match.","salary_min":200000,"salary_max":400000,"location":"San Francisco, CA","workplace":"onsite","remote_scope":"not_remote","job_type":"full-time","experience_level":"lead","tags":["llm","gpu","infrastructure","research"],"apply_url":"https://jobs.ashbyhq.com/inferact/3dee433c-7121-458c-8408-c193b6326ffb/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T20:04:02.323Z","expires_at":"2026-08-14T14:13:18.630914Z","created_at":"2026-07-09T14:11:07.184556Z","updated_at":"2026-07-15T14:13:18.737036Z","company_name":"Inferact","company_slug":"inferact","company_logo_url":"https://www.google.com/s2/favicons?domain=inferact.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/92eff494-6559-427b-8a18-9f3ed481a25a"},{"id":"f1bf694f-6890-4864-b7de-7d77bfbc9a49","company_id":"3da82454-107f-427f-88e7-01f315ef93fb","title":"Member of Technical Staff - GPU Infrastructure","slug":"member-of-technical-staff-gpu-infrastructure-63e3e8cc","description":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\nCore Technical Responsibilities\n\nThis customer-facing role combines deep technical expertise with hands-on implementation. You'll be instrumental in:\n\nCustomer Architecture \u0026 Design\n\n - Partner with clients to understand workload requirements and design optimal GPU cluster architectures\n\n - Create technical proposals and capacity planning for clusters ranging from 100 to 10,000+ GPUs\n\n - Develop deployment strategies for LLM training, inference, and HPC workloads\n\n - Present architectural recommendations to technical and executive stakeholders\n\nInfrastructure Deployment \u0026 Optimization\n\n - Deploy and configure orchestration systems including SLURM and Kubernetes for distributed workloads\n\n - Implement high-performance networking with InfiniBand, RoCE, and NVLink interconnects\n\n - Optimize GPU utilization, memory management, and inter-node communication\n\n - Configure parallel filesystems (Lustre, BeeGFS, GPFS) for optimal I/O performance\n\n - Tune system performance from kernel parameters to CUDA configurations\n\nProduction Operations \u0026 Support\n\n - Serve as primary technical escalation point for customer infrastructure issues\n\n - Diagnose and resolve complex problems across the full stack - hardware, drivers, networking, and software\n\n - Implement monitoring, alerting, and automated remediation systems\n\n - Provide 24/7 on-call support for critical customer deployments\n\n - Create runbooks and documentation for customer operations teams\n\nTechnical Requirements\n\nRequired Experience\n\n - 3+ years hands-on experience with GPU clusters and HPC environments\n\n - Deep expertise with SLURM and Kubernetes in production GPU settings\n\n - Proven experience with InfiniBand configuration and troubleshooting\n\n - Strong understanding of NVIDIA GPU architecture, CUDA ecosystem, and driver stack\n\n - Experience with infrastructure automation tools (Ansible, Terraform)\n\n - Proficiency in Python, Bash, and systems programming\n\n - Track record of customer-facing technical leadership\n\nInfrastructure Skills\n\n - NVIDIA driver installation and troubleshooting (CUDA, Fabric Manager, DCGM)\n\n - Container runtime configuration for GPUs (Docker, Containerd, Enroot)\n\n - Linux kernel tuning and performance optimization\n\n - Network topology design for AI workloads\n\n - Power and cooling requirements for high-density GPU deployments\n\nNice to Have\n\n - Experience with 1000+ GPU deployments\n\n - NVIDIA DGX, HGX, or SuperPOD certification\n\n - Distributed training frameworks (PyTorch FSDP, DeepSpeed, Megatron-LM)\n\n - ML framework optimization and profiling\n\n - Experience with AMD MI300 or Intel Gaudi accelerators\n\n - Contributions to open-source HPC/AI infrastructure projects\n\nGrowth Opportunity\n\nYou'll work directly with customers pushing the boundaries of AI, from startups training foundation models to enterprises deploying massive inference infrastructure. You'll collaborate with our world-class engineering team while having direct impact on systems powering the next generation of AI breakthroughs.\n\nWe value expertise and customer obsession - if you're passionate about building reliable, high-performance GPU infrastructure and have a track record of successful large-scale deployments, we want to talk to you.\n\nApply now and join us in our mission to democratize access to planetary scale computing.\n\nCompensation\n\nCash Compensation Range of $150-300k plus Equity Incentives","salary_min":150000,"salary_max":300000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"lead","tags":["distributed-systems","agents","llm","pytorch","generative-ai","gpu","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/PrimeIntellect/297d925e-5a42-40bd-b02f-5c928d226f18/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T18:45:18.934Z","expires_at":"2026-08-14T14:12:06.855135Z","created_at":"2026-04-13T15:01:32.586506Z","updated_at":"2026-07-15T14:12:06.981969Z","company_name":"Prime Intellect","company_slug":"PrimeIntellect","company_logo_url":"https://www.google.com/s2/favicons?domain=primeintellect.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/f1bf694f-6890-4864-b7de-7d77bfbc9a49"},{"id":"537b089a-1139-46c6-9166-2dc6b9693a2f","company_id":"3da82454-107f-427f-88e7-01f315ef93fb","title":"Research Engineer - RL Infrastructure ","slug":"research-engineer-rl-infrastructure-af69c92c","description":"OWN YOUR INTELLIGENCE\n\n\n\nPrime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.\n\n\n\nOur platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.\n\nWe train open frontier models and ship the same stack to our customers. Its spans the full stack of training, deploying and continuously improving models — compute, large-scale RL, environments, sandboxes, evals, and deployment.\n\n\n\nPrime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators — including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.\n\n\n\n\n\nWHAT YOU’LL WORK ON\n\n - Build and optimize the systems infrastructure behind large-scale RL and distributed training workloads by contributing to our prime-rl https://github.com/PrimeIntellect-ai/prime-rl framework.\n\n - Improve end-to-end training efficiency across compute, memory, networking, and scheduling layers.\n\n - Design and implement low-level performance optimizations, including kernels, communication paths, and runtime improvements.\n\n - Work on distributed training systems spanning data, tensor, and pipeline parallel workloads.\n\n - Help shape the architecture of our RL training stack, including async rollout and post-training systems.\n\n - Contribute to open-source libraries and internal infrastructure used for frontier-scale model training.\n\n - Collaborate closely with researchers and infrastructure engineers to translate bottlenecks into concrete systems improvements.\n\n - Stay at the frontier of training systems, inference systems, compiler/runtime tooling, and hardware-aware optimization techniques.\n\n\n\n\n\nYOU MAY BE A FIT IF YOU HAVE\n\n - Strong systems engineering experience in AI/ML infrastructure, especially around large-scale model training or inference.\n\n - Deep familiarity with PyTorch and distributed training frameworks such as PyTorch Distributed, DeepSpeed, FSDP, Megatron, vLLM, Ray, or related tooling.\n\n - Experience optimizing training performance across kernels, memory movement, communication overhead, or parallelization strategy.\n\n - Hands-on experience with large-scale training techniques including data parallelism, tensor parallelism, and pipeline parallelism.\n\n - Strong understanding of GPU architecture, profiling, and performance debugging.\n\n - Ability to identify bottlenecks across the stack and drive improvements from first principles.\n\n - Comfort working in a fast-moving environment with ambiguous problems and high ownership.\n\n\n\n\nESPECIALLY EXCITING\n\n - Experience writing or optimizing CUDA / Triton kernels.\n\n - Experience with compiler or runtime optimization for ML systems.\n\n - Experience working on RL training infrastructure, rollout systems, or asynchronous training pipelines.\n\n - Experience with multi-node GPU clusters and high-performance networking.\n\n - Contributions to open-source ML systems or infrastructure projects.\n\n - Interest in publishing technical work or sharing insights through engineering blogs and technical writing.\n\n\n\n\nWHY THIS ROLE MATTERS\n\nThe next frontier in AI will not be unlocked by models alone. It will be unlocked by systems that let those models train faster, adapt continuously, and operate across real environments at scale.\n\nThat infrastructure does not exist yet in the form the world needs.\n\nWe’re building it.\n\n\n\n\nBENEFITS \u0026 PERKS\n\n - Cash Compensation Range of $150-350k, plus equity.\n\n - Flexible work arrangements, with the option to work remotely or in person from our San Francisco office.\n\n - Visa sponsorship and relocation support for international candidates.\n\n - Quarterly team offsites, hackathons, conferences, and learning opportunities.\n\n - A deeply technical, high-agency team working on infrastructure for open superintelligence.\n\nIf you’re excited about building the systems foundation for frontier-scale RL an","salary_min":150000,"salary_max":350000,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["pytorch","gpu","search","distributed-systems","agents","llm","infrastructure","research"],"apply_url":"https://jobs.ashbyhq.com/PrimeIntellect/05e4b76b-2570-4c89-baf2-9833fff7378f/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T18:43:53.584Z","expires_at":"2026-08-14T14:12:07.380628Z","created_at":"2026-04-13T15:01:32.609376Z","updated_at":"2026-07-15T14:12:07.509749Z","company_name":"Prime Intellect","company_slug":"PrimeIntellect","company_logo_url":"https://www.google.com/s2/favicons?domain=primeintellect.ai\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/537b089a-1139-46c6-9166-2dc6b9693a2f"},{"id":"02d9b9e2-4ce6-4383-9790-004a3be256d8","company_id":"5d6de1f6-4d6c-463b-8a2b-a5caeadb97b4","title":"Senior Software Engineer - Airflow Infrastructure","slug":"senior-software-engineer-airflow-infrastructure-93378aa7","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\nAt Astronomer, we’re redefining how companies run Apache Airflow at scale. Our R\u0026D organization is home to some of the most innovative minds in cloud infrastructure and open-source software.\n\nWe’re looking for a Senior Software Engineer to join our Airflow Infra team, part of Astro, our flagship cloud platform. You’ll be building the critical layer that connects the open-source Airflow ecosystem to enterprise-grade, massively scalable cloud infrastructure. Your work will directly influence how global organizations orchestrate data pipelines at scale—making them faster, more reliable, and easier to manage.\n\nIf you’re driven by impact, excited by scale, and ready to work on the kind of infrastructure challenges that push the boundaries of what’s possible in cloud-native systems, this is the opportunity you’ve been waiting for.\n\n\n\n\nWHAT YOU GET TO DO:\n\n - Engineer backend services with high quality, maintainable and well tested code.\n\n - Partner with other engineers, product, customer reliability support, and leadership to achieve business goals and define how our systems should evolve.\n\n - Regularly engage in code reviews and provide constructive feedback.\n\n - Optimize the performance, reliability and scalability of existing backend services.\n\n - Investigate, prototype and propose ideas to improve user experience.\n\n - Create and maintain technical documentation for systems and processes, ensuring clarity and accessibility.\n\n - Participate in on-call rotation, troubleshoot and debug to solve incidents.\n\n\n\n\nWHAT YOU BRING TO THE ROLE:\n\n - 5+ years of experience building and delivering SaaS products.\n\n - Strong proficiency in Python, Golang and experience with Kubernetes.\n\n - Solid understanding of and experience with integrating with RESTful APIs and distributed systems.\n\n - Comfortable with testing frameworks, such as pytest.\n\n - Strong communication skills, both written and verbal, with experience in creating technical specifications.\n\n - A passion for reliability and operational excellence.\n\n - Ability to scope work and coordinate cross-functionally to address risks and ensure successful delivery.\n\n - Experience with software development best practices, such as code reviews, testing, CI/CD, version control, automation and debugging.\n\n - Ability to adjust to change and rapid pace of development.\n\n - Proactive approach to identifying and addressing issues, with a focus on ownership and accountability.\n\n\n\n\nBONUS POINTS IF YOU HAVE:\n\n - Experience with Apache Airflow\n\n\n\nThe estimated salary for this role ranges from $200,000 - $230,000 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 qualifications.\n\n\n\n#LI-Fulltime\n\n#LI-Hybrid\n\n\n\nAt Astronomer, we value diversity. We are an equal opportunity employer: we do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.","salary_min":200000,"salary_max":230000,"location":"New York, NY","workplace":"hybrid","remote_scope":"not_remote","job_type":"full-time","experience_level":"senior","tags":["cloud","distributed-systems","data-pipeline","infrastructure"],"apply_url":"https://jobs.ashbyhq.com/astronomer/9bb0bdfe-c4d6-45a1-9556-bbcd86ec76f6/application","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-08T17:42:58.635Z","expires_at":"2026-08-14T14:19:31.28307Z","created_at":"2026-07-09T14:16:54.84976Z","updated_at":"2026-07-15T14:19:31.377601Z","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/02d9b9e2-4ce6-4383-9790-004a3be256d8"},{"id":"cea172f2-7ff5-4ae5-9400-c763a96f22dc","company_id":"714f360f-a244-487d-b3f0-0c43518a9e66","title":"Sr. Data Scientist, Infrastructure","slug":"sr-data-scientist-infrastructure-269a1d04","description":"About Pinterest: \n Millions of people around the world come to our platform to find creative ideas, dream about new possibilities and plan for memories that will last a lifetime. At Pinterest, we’re on a mission to bring everyone the inspiration to create a life they love, and that starts with the people behind the product.\n Discover a career where you ignite innovation for millions, transform passion into growth opportunities, celebrate each other’s unique experiences and embrace the  flexibility to do your best work. Creating a career you love? It’s Possible.\n At Pinterest, AI isn't just a feature, it's a powerful partner that augments our creativity and amplifies our impact, and we’re looking for candidates who are excited to be a part of that. To get a complete picture of your experience and abilities, we’ll explore your foundational skills and how you collaborate with AI.\n Through our interview process, what matters most is that you can always explain your approach, showing us not just what you know, but how you think. You can read more about our AI interview philosophy and how we use AI in our recruiting process here .\n Pinterest brings millions of people the inspiration to create a life they love. Behind that experience is a complex infrastructure ecosystem that powers reliability, performance, measurement, and efficiency across the platform. As Pinterest grows, it’s increasingly important that we understand these systems clearly so we can make smarter decisions for both Pinners and the business.\n  \n We’re looking for a Data Scientist to join our Infrastructure Data Science team. In this role, you’ll partner with engineering and cross-functional teams to make Pinterest’s infrastructure more measurable, intelligible, and actionable. Depending on the area, your work may span app performance, shopping infrastructure, metrics quality, infrastructure governance, or site reliability. You’ll help build the data foundations, measurement systems, and analytical frameworks that enable Pinterest to optimize core technical systems and make better product and infrastructure decisions.\n  \n What you’ll do: \n In this role, you will partner closely with engineering and cross-functional teams to improve how Pinterest measures, understands, and optimizes its infrastructure:\n \n Partner with engineering teams to define, measure, and improve the health, quality, and efficiency of Pinterest’s infrastructure systems.\n Build and refine metrics, dashboards, and analytical frameworks that make complex technical systems more understandable and actionable.\n Strengthen data foundations by improving metric definitions, auditing data quality, and contributing to pipeline and measurement improvements where needed.\n Design and analyze experiments, investigations, and deep dives to quantify the impact of infrastructure changes on user experience, reliability, and business outcomes.\n Translate ambiguous technical problems into clear analyses and actionable recommendations for engineering and platform partners.\n Support high-priority investigations and decision-making related to infrastructure performance, reliability, cost, and measurement quality.\n Identify opportunities to improve how Pinterest measures and optimizes infrastructure across a range of domains, such as performance, shopping infrastructure, governance, metrics quality, and site reliability.\n \n  \n What we’re looking for: \n \n 4+ years of combined post-graduate academic and industry experience applying scientific methods to solve real-world problems with large-scale data.\n Bachelor’s/Master’s degree in a relevant field such as Computer Science, or equivalent experience.”\n Strong SQL and analytical programming skills, with experience working through messy, imperfect data and building reliable metrics and datasets.\n Experience partnering on or contributing to production-ready data pipelines, measurement systems, or foundational data work that improves data quality and usability.\n Solid foundation in experimentation and measurement, with the ability to design analyses, interpret results rigorously, and partner effectively with engineers and other cross-functional stakeholders.\n Demonstrated ability to translate ambiguous problems into clear analytical workstreams and actionable recommendations.\n Strong cross-functional communication skills, with the ability to explain technical findings clearly to engineering, product, and platform stakeholders.\n Ability to operate independently, prioritize across both longer-term projects and fast-turn inbound requests, and drive work forward in a dynamic environment.\n Curiosity and a builder mindset, with excitement for improving messy systems and creating more scalable, trustworthy measurement foundations.\n \n  \n In-Office Requirement Statement: \n \n We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs","salary_min":139764,"salary_max":287749,"location":"San Francisco, CA","workplace":"remote","remote_scope":"unknown","job_type":"full-time","experience_level":"senior","tags":["data-pipeline","devops","infrastructure","data-science"],"apply_url":"https://www.pinterestcareers.com/jobs/?gh_jid=8024966","is_featured":false,"is_sticky":false,"status":"active","published_at":"2026-07-07T20:19:01Z","expires_at":"2026-08-14T14:10:31.397303Z","created_at":"2026-07-09T14:08:38.685575Z","updated_at":"2026-07-15T14:10:31.532892Z","company_name":"Pinterest","company_slug":"pinterest","company_logo_url":"https://www.google.com/s2/favicons?domain=www.pinterest.com\u0026sz=128","quality_score":90,"url":"https://aidevboard.com/job/cea172f2-7ff5-4ae5-9400-c763a96f22dc"}],"market_demand_pack":{"amount_cents":2900,"api_checkout_url":"https://aidevboard.com/api/v1/checkout?product_id=aidevboard_ai_skills_demand_pack","checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","currency":"USD","description":"Full ranked public AI/ML demand CSV, source job URLs, and decision brief with market and offer angles.","fulfillment":"automatic_email_after_paid_checkout","human_checkout_url":"https://aidevboard.com/market-demand-pack?qc=api-jobs-market-demand-pack\u0026utm_campaign=skills_demand_pack\u0026utm_medium=jobs_api\u0026utm_source=api","name":"AI Market Demand Pack","next_step":"Open checkout_url for Stripe Checkout, or call api_checkout_url to get the non-charging checkout handoff payload.","price_usd":29,"product_id":"aidevboard_ai_skills_demand_pack","quote_url":"https://aidevboard.com/api/v1/quote?product_id=aidevboard_ai_skills_demand_pack"},"page":1,"per_page":20,"total":636,"total_pages":32}