Full Stack Software Engineer Application Development Manager in San Francisco

About the Team We're building the foundation for a new kind of AI coworker: persistent agents that have their own environments, can meet people wherever they work, and continue making progress for as long as a task requires. Our goal is to help individuals, teams, and organizations delegate meaningful work to AI—not just ask questions or complete a single turn. Our work brings together product, agent, and infrastructure capabilities across OpenAI. Together, we are creating always-on virtual coworkers that can carry context across tasks, operate through the right tools and channels, and deliver reliable results in real workplace environments. About the Role We’re looking for a full stack product engineer to shape how people discover, direct, and collaborate with AI coworkers. You’ll own product experiences end to end, spending roughly equal time building intuitive frontend surfaces and the backend systems that make agentic workflows persistent, reliable, and useful. You’ll work at the intersection of product engineering, design, agent capabilities, and enterprise readiness—turning rapidly evolving model and platform capabilities into experiences customers can understand, trust, and use every day. In this role, you will: Design, build, and ship full stack product experiences that help people and teams delegate meaningful work to persistent AI coworkers. Create intuitive frontend interfaces for directing agents, reviewing their progress, understanding their actions, and collaborating on the work they produce. Build backend APIs, services, and data models that support persistent agent state, asynchronous execution, orchestration, and progress reporting. Develop workflows that help agents access relevant context, use tools, and collaborate with people across workplace surfaces and channels. Partner with product, design, research, and engineering teams to turn shared capabilities into cohesive products. Build trust into the product through clear user controls, understanda

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 6.5 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $257M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. Applying to Render We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, an

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 6.5 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $257M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. Applying to Render We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, an

At Render, we’re building the modern cloud platform for developers creating AI-native, full-stack, multi-service applications. Our mission is to eliminate the tradeoff between the power of hyperscalers and the simplicity of developer-friendly platforms—so teams can ship fast, scale reliably, and focus on their product, not infrastructure. Unlike complex hyperscalers or ephemeral edge/serverless solutions, Render offers a developer-first experience with persistent compute, dynamic autoscaling, built-in orchestration, and observability, allowing teams to launch, scale, and manage real-world applications without writing infrastructure code or managing servers. Whether you're building LLM-powered applications, scalable SaaS products, or async processing pipelines, Render empowers teams to move fast and scale confidently from MVP to millions of users. Our platform is trusted by over 6.5 million developers worldwide and continues to grow rapidly. In February 2026, we raised an additional $100M in Series C financing, bringing our total funding to $257M, to accelerate our vision of making cloud infrastructure both powerful and intuitive—designed for the speed of modern AI development. We’re a diverse and talented team that values craft, velocity, and user experience. If you’re excited to help shape the future of the intelligent cloud and empower developers everywhere, we’d love to hear from you. Applying to Render We're seeking candidates who possess high integrity, humility, and an insatiable drive to learn. Through reasoned discussions and continuous feedback, we strive to improve both individually and collectively. We foster an environment of mutual trust and respect, empowering effective debate to achieve the best outcomes for our customers and team. We especially encourage members of underrepresented groups in the tech community to apply and understand that not all successful candidates will meet each requirement listed. Our interview process is unique to each role, an

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions tailored to the demands of advanced AI workloads. We work across the full stack—from silicon to system integration—partnering closely with internal teams and external vendors to define and deliver next-generation AI infrastructure. Our team focuses on defining scalable, high-performance system architectures and reference designs that balance performance, cost, and operational efficiency across rapidly evolving technologies. About the Role We are seeking a 3P Architect to define and drive rack- and cluster-level reference designs in collaboration with external partners. This role is responsible for translating workload requirements and system-level goals into concrete architectures, aligning partners on critical design attributes, and ensuring vendor roadmaps meet our infrastructure needs. You will work closely with performance modeling and internal architecture teams to evaluate tradeoffs, while owning the end-to-end definition and execution of third-party system designs. This includes identifying gaps in current technologies, driving vendor development, and shaping future infrastructure capabilities. This role requires strong system intuition, cross-functional leadership, and the ability to operate effectively across internal teams and external ecosystems. 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. Key Responsibilities Define rack- and cluster-level reference architectures for AI infrastructure deployments. Translate workload requirements into clear system design specifications and partner deliverables. Collaborate with performance modeling teams to evaluate architectural tradeoffs and system behaviors. Align internal stakeholders and external partners on critical system attributes (performance, cost, power, reliability, scalability). Identify gaps in current technology offerings and dr

About the Role As a member of the Data team within the Go-to-Market organization, you will help build a data-driven culture, improve decision-making, and advance strategic initiatives through analytics. This is a full-stack data role spanning data modeling, metric definition, visualization, analysis, and self-service tooling. You will build trusted, scalable data sources and products that give the business reliable, actionable insights. The work calls for judgment: you will choose the tool, approach, and level of investment that best fit each problem, from a focused analysis to a durable production data product. As a core partner to the GTM organization, you will address both foundational and ad hoc analytics needs. You will turn complex data into clear narratives that help technical and non-technical audiences understand what is happening, why it matters, and what they should do next. In This Role, You Will Partner closely with GTM teams to proactively identify high-impact questions and translate business needs into data models, metrics, analyses, and scalable technical solutions. Define, source, validate, and operationalize the metrics that guide the business, helping teams incorporate them into planning and day-to-day decisions. Lead cross-functional data projects across established and emerging business areas, including setting the data strategy for greenfield domains. Build scalable data models and pipelines that integrate and transform data from multiple sources into trusted, accessible datasets. Create dashboards, reports, analytical tools, and other data products that enable stakeholders to answer questions independently. Own the lifecycle of metrics, analytical models, and data products from initial exploration and prototyping through production and ongoing maintenance. Choose the most effective approach for each problem—whether an analysis, metric, data model, visualization, or self-service product—based on the audience, urgency, complexity, and expected v

About the team The Agent Enablement AI Deployment Engineering (ADE) team works across engineering, product, design, partnerships, and strategic customers to grow an open ecosystem of agent-enabled sites and services. We help partners adopt the OpenAI tech stack related to identity, permissioning, agent-auth primitives so users can safely connect ChatGPT and Codex to the tools, services, and workflows they already use. Our team also works with external partners on defining the standards for agent access, marketplace offerings as well as other agent enablement initiatives to ensure users of ChatGPT and Codex go from intent to task completion seamlessly. About the role We are looking for an AI Deployment Engineer to help strategic partners design, build, validate, launch, and operate agent enablement integrations across web applications, connectors, APIs, CLIs, MCP servers, and developer tools. This is a hands-on, partner-facing product engineering role for someone who can contribute to the platform itself, lead sophisticated technical engagements, and turn ambiguous identity and agent-workflow requirements into secure, production-ready integrations. You will work across partner product and engineering teams and OpenAI’s product, engineering, design, partnerships, legal, policy, security, support, and go-to-market teams. You will identify high-value user journeys, choose the right integration path, prototype and review architectures, write code, run evaluations and dogfood, trace failures end to end, guide launch and rollout, and support post-launch iteration. The best person for this role moves fluidly between full-stack code, OAuth/OIDC and identity systems, product judgment, project leadership, and clear communication with engineers and executives. This role is a fit for a product-minded engineer who wants to stay close to users and partners while going deep on authentication, permissions, reliability, safety, and developer experience. The principle objective is to

About the Team OpenAI’s Education team is building products that advance how people learn with AI. The team works across higher education institutions, K-12 districts, and country-level partnerships, including applied research on how AI affects learning and cognitive outcomes. The team owns owns ChatGPT Edu, ChatGPT for Teachers, and related product/research work. The team partners closely with go-to-market, research, Consumer Learning, and model teams to turn education-specific insights into product experiences that can improve ChatGPT more broadly. Some of our recent work: New Education Plugins for ChatGPT Work and Codex New tools for understanding AI and learning outcomes Education for countries Advancements in higher education Early product work - Introducing Study Mode About the Role We’re looking for a hands-on Tech Lead Manager to lead and manage a team of senior full-stack engineers building AI-native learning experiences in ChatGPT. This person will combine technical execution, product judgment, and people leadership: they will write and ship code, manage engineers, and help shape the product direction for how students and Educators use AI. In This Role, You Will Lead and manage a team of three senior full-stack engineers. Build product experiences for ChatGPT Education, ChatGPT for Teachers, and AI-native learning workflows. Partner with research teams on field studies, randomized control trials, classifiers, data pipelines, and cognitive-outcome measurement. Collaborate with Consumer Learning and model teams to translate education insights into broader ChatGPT behavior and product improvements. Drive execution across product, engineering, research, go-to-market, and partner teams. Help define product strategy, priorities, and delivery plans for a new product pod. You Might Thrive In This Role If You Have several years of direct people-management experience with engineers. Are still highly technical and comfortable doing IC engineering work. Have strong pr

About the Team The Artifacts team is building the AI-native creation layer for documents, spreadsheets, slide decks, dashboards, reports, analyses, and new forms of interactive work products. We are rethinking what creation looks like when models can move from an ambiguous user goal to a polished, editable artifact with strong structure, taste, correctness, and speed. This is a high-agency team working across product, infrastructure, and research. We partner closely with model training teams to shape how frontier models create artifacts, and with ChatGPT product teams to turn those capabilities into experiences that millions of people can use. The work spans full-stack product engineering, model integration, rendering and editing systems, collaboration, storage, evaluation loops, and production reliability. Our ambition is to build the premier product experience for AI-generated artifacts: starting with familiar work products like slides, sheets, and docs, then expanding into new artifact types that are only possible in an AI-native world. About the Role As Engineering Manager, Artifacts, you will lead and grow the engineering team responsible for building this product and technical foundation. You will manage a team of full-stack and infrastructure-oriented engineers, set technical direction, and stay hands-on enough to shape architecture and debug hard problems. This role sits at the intersection of product engineering, research, and infrastructure. You will partner with researchers on how models are trained and evaluated for artifact creation, with product and design on the user experience. This is a strong fit for a technical manager who wants to build and ship, not only coordinate. The team has a fast trajectory, so you will help define both the product surface and the team that builds it. In this role, you will: Lead, manage, and grow a team building AI-native artifact creation experiences across documents, spreadsheets, slide decks, and emerging artifact form

About the Team OpenAI's Enterprise team builds AI-powered enterprise products and shared platform capabilities that help organizations put advanced AI to work securely and at scale. Our work spans enterprise workflows, agent experiences, integrations, identity, administration, security, governance, and deployment. About the Role As a Technical Program Manager on Enterprise, you will lead the technical strategy and execution behind the products and shared capabilities that make ChatGPT, Codex, and future OpenAI products useful, secure, and scalable for organizations. You will translate customer needs, competitive dynamics, and product priorities into actionable plans, influence architectural direction, and deliver durable capabilities across application, platform, and infrastructure layers. The role requires deep technical fluency, strong product judgment, and the ability to move between hands-on execution and broader enterprise strategy. 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: Drive technical strategy and execution for enterprise product and AI workflow initiatives, from design through implementation, launch, customer rollout, and iteration. Partner with engineering teams to influence architectural direction, interface definitions, and implementation tradeoffs across full-stack products, APIs, integrations, and shared platform systems. Translate enterprise customer requirements into actionable product priorities across AI-powered workflows, agent experiences, integrations, permissions, data access, evaluations, identity, security, governance, and deployment readiness. Represent the needs of enterprise buyers, IT administrators, security teams, business leaders, developers, and end users in product and technical decisions. Identify adoption barriers, competitive gaps, and opportunities to make OpenAI products easier for organizations

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 Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

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 Is Different This is not a typical “Applied Scientist” or “ML Engineer” role. As a Member of Technical Staff, Applied ML, you will: Work directly with enterprise customers on problems that push LLMs to their limits. You’ll rapidly understand customer domains, design custom LLM solutions, and deliver production-ready models that solve high-value, real-world problems. Train and customize frontier models — not just use APIs. You’ll leverage Cohere’s full stack: CPT, post-training, retrieval + agent integrations, model evaluations, and SOTA modeling techniques. Influence the capabilities of Cohere’s foundation models. Techniques, datasets, evaluations, and insights you develop for customers will directly shape the next generation of Cohere’s frontier models. Operate with an early-startup level of ownership inside a frontier-model company. This role combines the breadth of an early-stage CTO with the infrastructure and scale of a deep-learning lab. Wear multiple hats, set a high technical bar, and define what Applied ML at Cohere becomes. Few roles in the industry combine application, research, customer-facing engineeri

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the role Forward Deployed Engineers (FDEs) lead complex end-to-end deployments of frontier models in production alongside our most strategic customers. You will own discovery, technical scoping, system design, build, and production rollout, partnering directly with customer engineering and domain teams. You will measure success through production adoption, measurable workflow impact, and eval-driven feedback that changes product and model roadmaps. You’ll work closely with our Product, Research, Partnerships, GRC, Security, and GTM teams. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role you will Own technical delivery across multiple deployments from first prototype to stable production Build full-stack systems that deliver customer value and sharpen how we learn Embed closely with customer teams, understand their needs, and guide adoption of what you build Scope work, sequence delivery, and remove blockers early Make trade-offs between scope, speed, and quality; adjust plans to protect delivery Contribute directly in the code when progress or clarity depends on it Codify working patterns into tools, playbooks, or building blocks that others can use Share field feedback that helps Research and Product understand where the models succeed and where they can improve Keep teams moving through clarity and follow-through You might thrive in this role if you Bring 5+ years of engineering or technical deployment experience that includes customer-facing work Have scoped and delivered complex systems in fast-moving or ambiguous environments Write and review production-grade code across frontend and backend using Python, JavaScript,

About the Team The Premium team owns some of the highest-leverage customer-facing levers in ChatGPT’s consumer revenue business, spanning the paid customer journey: helping users understand the value of paid plans, convert with confidence, and continue finding lasting value in their subscription. Our work is highly cross-functional, partnering with Product, Data Science, Design, FinEng, Finance, Legal, Support, and Marketing to improve free-to-paid conversion, renewal, customer lifetime value, and revenue while keeping the experience trustworthy, scalable, and low-friction. In This Role, You Will: Lead and scale an engineering team responsible for some of ChatGPT’s most important subscription and monetization experiences. Own the technical execution for Premium customer experiences across plan merchandising, paywalls, upgrade flows, checkout UX, plan management, renewals, downgrades, and cancellation. Partner with Product and Data Science to run high-quality experiments across upgrade, trial, renewal, downgrade, and cancellation flows. Improve key subscription metrics including conversion, renewal, churn, ARPU, and lifetime value. Build reliable customer-facing Premium experiences for purchase, plan management, renewal, downgrade, cancellation, and access-related states at scale. Partner closely with FinEng and other platform teams to evolve the billing, payments, and entitlement capabilities that power Premium experiences. Collaborate closely with Product, Design, Data Science, Finance, Legal, Support, and Marketing on monetization strategy and execution. You Might Thrive in This Role If You: Have 5+ years of engineering management experience, Have strong technical expertise in backend, frontend, or full-stack development, with experience building growth-oriented features. Have a track record of improving conversion, retention, or monetization through experimentation and data-driven product engineering. Are experienced with subscription products, plan merchandising

About the Team OpenAI’s acquisition of io marks our entry into consumer hardware and our ambition to define the next human–computer interface. Success in hardware requires strong financial stewardship across the full product cost stack—from early design and sourcing decisions through manufacturing, logistics, inventory, returns, and warranty. Hardware Finance works across Product, Supply Chain, Operations, Accounting, Systems/Data, and Finance to connect business decisions to product cost, inventory, cash, COGS, and margin. About the Role We are seeking a Hardware Finance Manager to own an assigned area of hardware COGS and inventory end to end. The initial assignment will depend on business priorities and the successful candidate’s expertise. It may include BOM and product cost, manufacturing variance analysis, inventory planning, logistics, returns and warranty, customer support, or another connected set of hardware-finance responsibilities. This is an individual-contributor role with broad scope. Prior hardware experience and deep, hands-on expertise in at least two relevant domains are required. The person will be expected to operate independently, build reusable processes and analytical workflows, and remain accountable for the analysis, judgment, and recommendations. In this role, you will: Own an assigned area of hardware COGS and inventory end to end. Own forecasting, close, and business variance analysis for the assigned scope. Provide hardware leadership with clear variance explanations, trend analysis, and forward-looking signals that connect business and supplier decisions to inventory, cash, COGS, and margin. Partner with business teams and Finance Platforms to establish the financial data, systems, and dashboards needed to support analysis. Ensure data integrity and governance through clear definitions, ownership, validation checks, controls, and review processes. Improve forecasting, reporting, systems, and finance processes so they remain reliable an