Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this role? We're building the foundational infrastructure that will define how the world thinks about and deploys AI, and we want the sharpest, most curious people to help us do it. As a Data Scientist on our Analytics and Data Insights team, you'll work on problems that don't have textbook answers yet; building the analytics that shape product and company strategy, designing the experiments that prove or kill our biggest bets, and helping enterprise customers understand what foundational AI actually means for their bottom line. You'll own analytical work end-to-end: from framing the right questions and building the models to shipping insights, tools, and results that product leaders, sales teams, and enterprise customers rely on. As a Data Scientist, you will: Drive the mission forward. Build bleeding-edge agentic analytics: Agentic analytics is far from a solved problem, and we want to be the company that solves it. We need the sharpest minds with the curiosity, drive, and focus required to build the tools necessary to bring order and clarity to real world data. Define AI impact measurement: own the end-to-end analytics st
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People Programs Lead in San Francisco
510 active opportunities · Updated October 2026
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Explore current people programs lead jobs in San Francisco. Filter by work mode, employment type, experience, department, date posted and distance.
Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this team? The GPU Clusters team builds and operates the superclusters that train Cohere’s frontier models. We sit at the intersection of hardware, distributed systems, and AI research. We work with cloud providers, researchers, and other infrastructure teams on problems few companies get to take on. As an Engineering Manager, you’ll lead a team of engineers who care deeply about GPU infrastructure. You’ll set technical direction, grow people, and help the company scale a rapidly growing compute footprint. As an Engineering Manager, you will: Hire, mentor, and grow a team of GPU infrastructure engineers , including performance, career development, and technical guidance on hard infrastructure problems Own the technical roadmap for the fleet: how we deploy, operate, and scale Kubernetes clusters, including workload scheduling, hardware fault detection, and performance Partner with researchers and ML engineers so the training and inference stack works well on new GPU architectures Work with cross-functional stakeholders such as Capacity, Finance, Legal, Security, and other infrastructure teams on planning, cost, compliance, an
$150K – $190K/yr
About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role The Developer Experience team is growing in San Francisco! This is a hybrid role out of our main headquarters and must be based there. We’re looking for a hands-on builder with strong opinions on great developer docs. Are you someone who loves tinkering with the newest features in your favorite products? Do you enjoy taking the next random JavaScript framework for a spin and figuring out how to make them tick? Does it especially irk you when the code snippets are wrong, or the only docs for a feature are on X? Developer Experience at Sentry lives in the intersection of shipping really cool products and getting developers set up to use them. If you’re someone who is confident in partnering with Product and Engineering to test and ship the latest features, not afraid to jump in and go hands-on to solve problems for our biggest customers, and a good eye for what good docs looks like - this is a dream role. Developer Experience at Sentry is a team of builders who are constantly looking for ways to make it easier for every developer to use Sentry. We engage with the challenges facing technical communities, to support developers, gather feedback, and help our product and engineering teams ship new capabilities. An engineer in this role should be confident to “come with an answer," propose the product solutions, identify the content and/or execution plans and people to partner with, and go execute. In this role you will Attend and even host events and meetups in the developer community Have a point of view and aren’t shy about expressing it. You get your energy from both knowing the latest trends and having a POV on
About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n
About PostHog Product development used to mean manually writing code, running analysis, diagnosing bugs, and rolling out changes using dozens of tools. PostHog is the only platform that acts like a co-pilot for you (and your AI agents) to do it all – autonomously. We started with open-source product analytics, launched out of Y Combinator's W20 cohort . We've since shipped more than a dozen products , including: PostHog Code , the only AI devtool that understands your product, not just your codebase. A built-in data warehouse , so users can query product and customer data together using custom SQL insights. PostHog AI , an AI-powered analyst that answers product questions, helps users find useful session recordings, and writes custom SQL queries. We are: Product-led . More than 450,000 organizations have installed PostHog, mostly driven by word-of-mouth. We have intensely strong product-market fit. Default alive . Revenue is growing incredibly quickly, and we're very efficient. We raise money to push ambition and grow faster, not to keep the lights on. Well-funded. We've raised more than $180m from some of the world's top investors. We're set up for a long, ambitious journey. We're focused on building an awesome product for end users, hiring exceptional teammates, shipping fast, and being as weird as possible . Things we care about Transparency: Everyone can read about our roadmap, how we pay (or even let go of) people, our strategy, and how we work, in our public company handbook . Internally, we share revenue, notes and slides from board meetings, and fundraising plans, so everyone has the context they need to make good decisions. Autonomy: We don’t tell anyone what to do. Everyone chooses what to work on next based on what's going to have the biggest impact on our customers, and what they find interesting and motivating to work on. Engineers lead product teams and make product decisions . Teams are flexible and easy to change when needed. Shipping fast: Why not n
From $200K/yr
We are looking for a talented engineer to lead evaluation of startup acquisition opportunities in the AI, cloud and security space. You will drive product evaluations, prepare and manage technical architecture discussions with target groups in Product and Engineering and provide roadmap suggestions for M&A and investments for Datadog. You will be a key partner to Datadog’s C-level leadership and highly visible at the most senior levels of Datadog. The role is reporting into the Senior Director of Product Strategy and falls within the Product organization. We are looking for an innovative and strategic thinker who is passionate about the latest tech being developed by startups in the cloud, AI and security space. The ideal candidate enjoys researching and evaluating new technologies, works effectively with cross-functional teams, and communicates opinions concisely to our leadership team. Broad understanding of relevant Cloud Technologies and deep understanding of the full coverage of Datadogs current offerings is necessary. The Corporate Development team is small and values authentic, strong-willed individuals who think creatively and proactively. This role leads technical due diligence from a product and architecture perspective across our acquisition pipeline. You'll scope and stand up proof-of-concept and sandbox environments to stress-test candidate products, then give an honest, unvarnished view of their quality and depth - the kind of assessment that holds up regardless of deal momentum. You'll assess technical architecture, flag the risks and open questions that matter most early, and turn that into a clear post-acquisition integration path. Working closely with engineering, you'll keep the evaluation focused on what's actually decision-relevant, then translate the findings into strategic recommendations for leadership and help carry the integration through by partnering with the right people on the other side. What You’l
From $90K/yr
Mid-Market Account Executive As an Account Executive on our Mid-Market Sales team, you will assist in Datadog’s overall business growth by strategically engaging and closing net-new customers across mid-to-large size organizations. Sellers follow a well-defined methodology, collaborate with internal stakeholders, identify the customer's unique needs, and clearly convey the value of the Datadog product. Mid-Market reps have the opportunity to grow their careers in Sales and continue contributing to Datadog team success. At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them. What You’ll Do: Focus entirely on net-new logo acquisition Convert inbound leads to closed opportunities Leverage tools such as Sales Navigator and DiscoverOrg Strategically prospect into Chief Technology Officers, Engineering/IT Leaders, and technical end users (SRE, DevOps, DevSecOps) Multi-thread into different departments of a complex organization Collaborate with Sales Development Representatives to drive top of funnel activity Manage the full sales cycle, including negotiations and on-site technical demonstrations Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your experience, we encourage you to apply. Who You Are: Experienced in hunting and closing net new logos Able to strategically map out and break into large scale organizations Curious, motivated, and driven as a sales person Bold on the phones and creative in your emails Able to sit up to 6 hours, traveling to and from client sites via auto, train, or air, up to 30% of the time Benefits and Growth: High income earning opportunities based on self performance Opportunity for Presidents C
About the Team At OpenAI, our User Safety & Risk Operations (USRO) team helps protect our products and users from abuse, fraud, safety risks, and other forms of misuse. We translate real-world user and operational signals into timely decisions, practical interventions, and improvements to our products and systems. This role will take on new, ambiguous, or underdeveloped operational risks and help mature them into scalable capabilities. We work across USRO and partner closely with Product, Engineering, Data Science, Product Policy, Legal, Safety, Support, and external vendors or partnership stakeholders. About the Role We are seeking a Senior Operations Analyst to take on complex, ambiguous safety and risk problems and turn them into practical operational solutions that can scale. This is a senior individual-contributor role for a versatile operator who is comfortable moving between queues, investigation, analysis, workflow design, hands-on execution, and cross-functional leadership. Depending on team needs, the role may focus on emerging-risk incubation, cloud deployment partnerships, or other new operational areas. You will be expected to move quickly, work hands-on, and create structure without waiting for perfect requirements or a large support team. The work starts with the problem, not a prescribed process. You may investigate unstructured user signals, stand up a lightweight workflow, build an AI-assisted tool, improve an existing operation, or help a new launch become operationally ready. The goal is to produce durable systems that other people can run, not simply complete a series of individual tasks. The portfolio will change with company priorities and may span established harm areas, emerging-risk incubation, cloud deployments and partnerships, device safety, or new product launches. Some hires may focus primarily on cloud deployment operations, including launch readiness, partner coordination, safety workflows, and operational monitoring. You will ty
About the team Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. Mitigating the frontier risks resulting from these capabilities is paramount to OpenAI’s ability to continue deploying models safely. The Preparedness team is dedicated to addressing these critical risks. Our work includes: Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. Mitigation. Keeping misalignment safeguards, alignment tools, and on track to adequately address extreme threats that might arise in the future. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework , and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. About the role Preparedness is hiring strong technical executors to support preparations for accelerated AI development, which may culminate in recursive self-improvement. This work relies on anticipating misalignment risks that might exist in the future, but might not exist now; so it’s especially important that people in this role are tasteful and strategic. The role is wide-ranging, covering any mitigation for loss of control risk, spanning the design and implementation of better pre-deployment risk-assessment , control measures , RSI-relevant training interventions, and turning one’s technical work into established institutional practices and external-facing communications. Below is a subset of our focus areas: Scalable oversight: Establishing practices for model misbehavior monitoring and oversight which remain effective in superhuman model capability regimes, with a focus on bridging from today’s monitoring approaches to future-proof ones. Automated auditing: As model capabilities increase, we’ll increasingly rely on automated approaches for finding the most severe forms of model misalignments. We’ll both need to s
About the Team OpenAI is at the center of some of the highest-impact multimodal work in AI. ChatGPT serves a massive global audience, and enables diverse interactions via text, speech, and visuals. As interactive surfaces grow, models also need to adapt to emerging harm, understand user intent and situational context, and respond appropriately. The Chat and Multimodal Safety team is responsible for ensuring that OpenAI’s increasingly multimodal models and products behave safely across these experiences. We develop the research, training methods, and evaluations needed to make these experiences safe. Our work sits at the frontier of responsibly deploying powerful AI, in close partnership with Personal AGI, io, model training, and product teams. About the Role As a Researcher on the Chat and Multimodal Safety team, you will help shape how frontier models perceive and reason the world, and translate that understanding into safe behavior. We’re looking for people who combine deep technical expertise with strong safety judgment. Strong candidates often bridge perception and language: they may have built vision-language models, worked on modality fusion or image encoders, developed multimodal post-training or evaluations, or advanced safety for image, video, or audio systems. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Define and advance multimodal safety research for text, vision, and audio, connecting perception and semantic understanding to safe model behavior. Build training and evaluation methods for VLMs, including post-training, safety evals, and interventions that help models respond safely and appropriately in varied contexts. Collaborate closely with Personal AGI, Consumer Devices, and product/model teams to translate research into safer ambient, embedded, and personalized multimodal experiences. You might thrive in this role if you:
About the Team The legal industry team works with law firms, in-house legal departments, legal technology companies, and other members of the legal ecosystem to understand how AI can support serious professional work. The team collaborates across Product, Research, Engineering, Design, Go-to-Market, Partnerships, Safety, Security, and Legal. We believe the strongest progress in legal will be built with the ecosystem. Our goal is to help customers and partners use OpenAI's capabilities in ways that are useful, trustworthy, and complementary to the products, expertise, and relationships that already serve the field. About the Role As a Product Manager you will help lead OpenAI's work with the legal industry. This is a high-ownership, hands-on role for someone who can turn incomplete information into clear priorities and shipped work. We’re looking for people who will spend time with customers and partners, work closely with researchers, engineers, designers, and operators, and keep complex work moving across teams. You will have meaningful ownership, but your success will depend as much on collaboration, follow-through, and judgment as on strategy. Success will depend on detailed, behind-the-scenes work in a fast-moving environment that can sometimes be chaotic. The right person will work very hard, get their hands dirty, and stay calm when the path is unclear. The work is also important and substantive: you will help shape how powerful technology is used in a consequential profession. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Turn customer, partner, market, and model evidence into a clear product strategy and roadmap for OpenAI’s work with the legal industry—including what to build, what not to build, and where ecosystem partners should lead. Define requirements and take products from early concept through real-world use and iteration.
About the Team The Support team is central to ensuring that our customers' experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. About the Role As a Product Engagement Specialist on the User Operations team you will be a hands-on systems builder responsible for making product launches and frontline feedback more scaleable, measurable and actionable across both internal User Operations and external third-party teams. You’ll be responsible for not only managing the project timelines, but also designing and shipping the workflows, tooling and data systems that connect the voice of the user into actionable improvements for Product and Engineering teams. We’re looking for people who thrive at the intersection of project management, team enablement, and customer advocacy, and enjoy working cross-functionally in a fast-paced, evolving environment. We are also looking for individuals that will not just do the day to day work - but will also be deeply involved in architecting the systems of feedback sharing and collection with our stakeholder groups across Support, Product, and Engineering. Think data systems, not better slide decks. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and own scalable systems for launch readiness, feedback capture, triage, synthesis, and routing. Coordinate product launches across internal User Operations teams and external third party teams to ensure seamless execution and support read
About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a
About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities Help bui
About the Team Security is at the foundation of OpenAI's mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect model weights, customer data, and critical systems across multiple cloud environments. The team partners across OpenAI, including Applied Engineering, Research, IT, Security, Infrastructure, and Engineering, to provide secure and scalable platforms for identity, access management, permissioning, orchestration, and safe AI research. About the Role We’re looking for an engineering leader to lead Identity Infrastructure Engineering, the team building the systems that govern and scale access across OpenAI’s research, engineering, and internal platforms. This role sits at the center of cloud infrastructure, identity, software engineering, and security-critical operations. You’ll lead engineers building control planes, policy systems, workload and agent authorization patterns, infrastructure-as-code, and operational foundations that help OpenAI move quickly while keeping access reliable, auditable, least-privileged, and safe under failure. The ideal candidate has led teams responsible for large-scale, mission-critical infrastructure. They can go deep into code and architecture when needed, while giving engineers and technical leads the clarity and ownership to do their best work. They set technical direction, grow strong teams, make durable architecture decisions, and turn ambiguous 0-to-1 problems into platforms OpenAI can trust and build on for years. In this role, you will: Build and lead a high-performing Identity Infrastructure team, going deep enough technically to set direction while empowering the team to own delivery. Define the strategy for identity platform as the policy plane for access across people, agents, workloads, services, clouds, and internal systems. Scale Acc
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