Platform Engineer, Forward Deployed Engineering (FDE) -SF

About the team OpenAI’s Forward Deployed Engineering (FDE) org sits at the intersection of product, engineering, research, and go-to-market. We take frontier platform capabilities into the real world with design partners, turning raw customer signal into shipped software, repeatable patterns, and product direction. This group is an innovation loop within FDE. We sprint on a small number of platform bets at a time: identify high-signal problems emerging across deployments, build early versions quickly, validate them with design partners, and work with our core engineering and product counterparts to put successful bets on a scalable path. When a capability is ready to scale, we help transition ownership — and then move on to the next frontier. About the role Platform Engineer is a role within Forward Deployed Engineering (FDE) for strong software and ML engineers who want to build new platform capabilities from scratch, grounded in real customer deployments. You’ll join a small team working in pods against platform bets rather than a single long-running account. You’ll collaborate closely with customer-tagged FDEs and partner teams across engineering and product to: (1) incubate early versions, (2) validate them with design partners through short deployments or pilots, and (3) drive adoption by making the capability durable, usable, and ready to scale. You should expect to be customer-facing when it matters – pitching, rollout planning, debugging, and learning directly from what breaks in production – but your primary charter is to turn frontier signal into reusable platform capability. This role does not require travel. It is based in San Francisco or New York. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel is optional-by-project and typically In this role you will Architect and build new platform capabilities: turn frontier customer signal into concrete designs, implementations, and APIs that become part of the OpenAI platform. Incubate platform bets end-to-end: take ambiguous problems, form a crisp hypothesis, ship an initial capability, and iterate quickly based on what breaks in real usage. Embed with design partners to learn fast: get close to production constraints, run deep technical discovery, and translate needs into product and platform requirements. Partner with customer-tagged FDEs in the field: deploy and debug together, capture repeatable patterns, and convert field learnings into platform improvements. Design and run pilot programs: define qualification criteria for early adopters, stand up internal/external alphas, and use pilots to harden both the platform and the rollout playbook. Collaborate as part of cross-functional platform teams: partner closely with core product and engineering counterparts, often as a single virtual team, to align on architecture and get to production together. Drive adoption outcomes: measure usage, identify blockers and failure modes, and prioritize the next platform increments that unlock repeatable value. You might thrive in this role if you Bring 5+ years of software engineering or ML engineering experience with a track record of shipping 0→1 capabilities that other engineers or customers depend on. Experience in high-ambiguity, fast-iteration environments (startups or product-centric teams) is a plus. Have owned customer-adjacent technical work end-to-end, from scoping and hypothesis-setting through production adoption, and improved outcomes through structured iteration (instrumentation, evals, error analysis, and tightening success criteria over time). Have built or operated systems where reliability, security, and governance materially shaped design (permissions/RBAC, auditability, data access boundaries, rollout safety, observability, and incident-driven hardening). Communicate clearly across engineering, product, go-to-market, and executive audiences , simplifying complex ideas and translating technical tradeoffs into adoption impact, sequencing decisions, and measurable outcomes. You can credibly “pitch” a platform bet in a customer conversation. Default to systems thinking: you turn ambiguous feedback, failures, and escalations into durable product requirements and reusable platform capabilities , not one-off fixes or bespoke delivery work. About OpenAI OpenAI 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. We 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. For additional information, please see OpenAI’s Affiantive Action and Equal Employment Opportunity Policy Statement. Background 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. 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