OpenAI · 채용 중 729건
Tech Lead, Finance & Supply Chain Engineering
Tech Lead, Finance & Supply Chain Engineering
재무정규직리드 · 경력 무관
OpenAI에서 재무 및 공급망 엔지니어링 팀을 이끌 테크 리드를 채용합니다. 풀스택 개발 및 데이터 엔지니어링 역량을 바탕으로 복잡한 시스템 아키텍처를 설계하고, AI 기반 워크플로우를 구축하는 핵심 역할을 수행합니다. Staff급 이상의 엔지니어링 경험과 기술적 영향력을 통해 팀의 기술 수준을 높이고, 유관 부서와 협력하여 비즈니스 가치를 창출할 분을 찾습니다.
The Finance & Supply Chain Engineering organization includes two complementary teams. Software Engineering builds internal full-stack applications, durable agentic workflows, plugins, MCPs, and measurable AI-enabled engineering practices. Data Engineering builds trusted analytics data assets for Finance and Supply Chain. The teams have distinct charters, with important shared dependencies and broad cross team partnerships across Engineering, Applications, Finance, and Supply Chain.
We are looking for a hands-on senior technical leader who will report alongside the Software Engineering and Data Engineering managers. This is an individual-contributor role with no immediate people-management responsibility. The Tech Lead will raise the technical bar across both teams, participate in important cross-team or high-risk design decisions, and directly own and ship high-impact work. The role should improve team judgment and autonomy rather than act as a floating architect or universal approval gate.
Partner with the Software Engineering and Data Engineering managers as a peer technical leader; managers retain accountability for people, staffing, priorities, performance, and delivery commitments.
Directly own the architecture, implementation, launch, and operation of one or more high-impact initiatives, remaining accountable for real outcomes rather than advisory output alone.
Guide important design decisions that are cross-team, difficult to reverse, or material to security, financial controls, reliability, data quality, or long-term cost of ownership.
Establish pragmatic engineering standards across architecture, APIs and data contracts, testing, security, reliability, observability, lineage, data quality, and operational ownership.
Advance engineering standards for building with AI, including agentic workflows, evaluation, telemetry, adoption, and outcome measurement.
Work across backend, full-stack, data, and big-data systems, making sound boundary decisions and bringing the right domain experts into the design.
Partner deeply with Engineering, Applications, Product, Finance, Supply Chain, Security, and other stakeholders to translate ambiguous needs into durable technical systems.
Raise the technical capability of both teams through design reviews, code reviews, mentoring, written guidance, and reusable reference implementations.
Protect team autonomy: focus involvement on consequential decisions, clarify principles and tradeoffs, and avoid becoming a required approver for routine or reversible work.
Have significant professional engineering experience with sustained staff-level or equivalent impact as an individual contributor; prior people management is not required, but a plus.
Can reason across a full-stack application—from user experience and client architecture through backend services, integrations, authorization, and durable state.
Have strong data-engineering judgment across analytical modeling, batch or streaming pipelines, orchestration, lineage, quality, scale, and downstream data contracts.
Have personally designed, built, shipped, and operated consequential systems, and can go from architecture to implementation details without relying on positional authority.
Have led important technical decisions and cross-team initiatives through influence, clear reasoning, and trusted partnership.
Care deeply about correctness, security, data quality, auditability, operational excellence, and measurable outcomes.
Communicate clearly with engineers, managers, and non-technical partners; lead with context and principles rather than control.
Experience building internal products, developer platforms, workflow systems, or analytics platforms used across multiple teams.
Experience with LLM applications, durable agents, AI evaluations, plugins, MCPs, or measurement of AI-enabled engineering outcomes.
Experience in Finance, Supply Chain, accounting, procurement, ERP, or another domain where controls, reconciliation, and traceability matter.
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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