# Tech Lead, Finance & Supply Chain Engineering

**Company:** [OpenAI](https://hotfix.jobs/companies/openai)
**Location:** San Francisco, CA
**Role:** Engineering Management
**Salary:** $230k – $385k/yr
**Experience:** 7+ years
**Skills:** Full Stack Development, Data Engineering, Backend Systems, Big Data, AI Workflows, Llm Applications, Agentic Systems, Data Pipelines, Observability, Security, Data Quality, Lineage
**Posted:** 2026-07-10

> Tech Lead partnering with Software and Data Engineering managers at OpenAI to raise technical standards, own high-impact architecture and implementation across full-stack, data, and AI systems for Finance and Supply Chain. Requires staff-level IC impact, full-stack and data engineering expertise, and strong influence without direct reports.

## Job Description

## Responsibilities
- Partner with the Software Engineering and Data Engineering managers as a peer technical leader.
- Directly own the architecture, implementation, launch, and operation of one or more high-impact initiatives.
- 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 by focusing involvement on consequential decisions, clarifying principles and tradeoffs.

## Requirements
- Significant professional engineering experience with sustained staff-level or equivalent impact as an individual contributor.
- Ability to reason across a full-stack application—from user experience and client architecture through backend services, integrations, authorization, and durable state.
- Strong data-engineering judgment across analytical modeling, batch or streaming pipelines, orchestration, lineage, quality, scale, and downstream data contracts.
- Personally designed, built, shipped, and operated consequential systems, and can go from architecture to implementation details without relying on positional authority.
- 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.

## Nice-to-Haves
- 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.

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