Forward Deployed Engineer, Legal

About the role

OpenAI's Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems, embedding with users to solve high-leverage problems and moving quickly from prototype to deployment. This role builds and deploys AI systems for legal work, embedding with customers and often with senior legal practitioners to find the right first use case, prototype a solution and prove measurable value. It is based in San Francisco or New York City, with a hybrid model of three days in the office per week, relocation assistance and possible travel of up to 50%.

Key responsibilities

• Embed with law firms and legal teams to understand workflows, identify high-value opportunities and choose the right initial use cases.
• Build full-stack systems that deliver customer value and help sharpen how the team learns.
• Work closely with customer teams, understand their needs and guide adoption of what you build.
• Balance scope, speed and quality, adjusting 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 others can use.
• Share field feedback so Research and Product know where models succeed and where they can improve.

Required profile

• 5+ years of software engineering, ML engineering or technical deployment experience with customer-facing ownership in financial services or adjacent regulated industries.
• Experience with legal technology, legal services, compliance-heavy workflows or professional services is helpful but not required.
• Owned complex AI or data-driven systems end-to-end, in environments where errors carry real financial or regulatory consequences.
• Deployed systems powered by LLMs or generative models and understands how model behavior, evaluation and guardrails affect trust and business outcomes.
• Able to communicate across engineering, product, risk, compliance and executive stakeholders.

Required skills

• Production-grade code writing and review across backend and frontend systems using Python, JavaScript or comparable stacks.
• Systems thinking and high execution standards.