Platform Engineer, Forward Deployed Engineering (FDE) - NYC
데브옵스 엔지니어정규직시니어 · 5년 이상
OpenAI는 Forward Deployed Engineering(FDE) 팀에서 플랫폼 엔지니어를 채용합니다. 5년 이상의 소프트웨어/ML 엔지니어링 경력을 바탕으로 고객 현장에서의 요구사항을 0에서 1로 제품화하고, 재사용 가능한 플랫폼 기능을 설계 및 구축하는 핵심 역할을 수행합니다. 시스템 사고와 기술적 리더십을 통해 엔지니어링 품질을 높이고 비즈니스 임팩트를 창출할 분을 찾습니다.
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 durable products.
The FDE Platform team is primarily a leverage function that scales the FDE org’s impact to OpenAI’s platform and products. We provide hands-on leverage by embedding with customer-tagged FDE pods to aid in architecting, product shaping, refactoring, and building. This team is perfect for highly collaborative software engineers who love innovating on cutting-edge products with other builders.
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 will partner with customer-tagged FDEs who are driving delivery and customer outcomes, and embed where you can provide the highest leverage. In practice that means working in the trenches on architecture, product shaping, refactoring, hardening, and reusable abstractions, while preserving the pod’s ownership of customer understanding and day-to-day execution. You will also collaborate closely with our B2B Platform Team and other long-term owners to align early on what should generalize, what should remain customer-specific, and what “ready for handoff” looks like.
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 <10%, with occasional spikes for key embeds or launches.
Provide hands-on leverage to customer pods: embed with customer-tagged FDE teams to support generalization, contributing directly in architecture, product shaping, refactoring, and implementation.
Turn repeated signals into platform bets: translate cross-customer patterns into crisp hypotheses with clear success criteria, scope, and a validation plan that fits real account constraints.
Raise the engineering bar through tooling and mentorship: set org-wide quality norms through high-signal code review and pairing, and build lightweight developer tooling that makes good architecture, readability, and correctness the default across FDE.
Collaborate as part of cross-functional platform teams: partner closely with B2B Product, customer-tagged FDEs, ops, and business partners to bring the right products and platform capabilities to market.
Lead complex platform capabilities end-to-end when needed: for high-leverage primitives like our Context Platform, act as DRI from requirements through implementation, make key tradeoffs explicit, and pull in customer pods early to keep the work grounded in real deployments.
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.
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.
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