Forward Deployed Engineer

🇺🇸 San Francisco, California
$1K - $5K Annual
Posted 2 months ago
Expires June 9, 2026

ABOUT MERCOR

Mercor is defining the future of work. We partner with leading AI labs and enterprises to provide the human intelligence essential to AI development.

Our vast talent network trains frontier AI models in the same way teachers teach students: by sharing knowledge, experience, and context that can't be captured in code alone. Today, more than 30,000 experts in our network collectively earn over $2 million a day.

Mercor is creating a new category of work where expertise powers AI advancement. Achieving this requires an ambitious, fast-paced and deeply committed team. You’ll work alongside researchers, operators, and AI companies at the forefront of shaping the systems that are redefining society.

Mercor is a profitable Series C company valued at $10 billion. We work in-person five days a week in our San Francisco, NYC, or London offices.

About the Role

As a Forward Deployed Engineer at Mercor, you’ll operate at the intersection of engineering, product, and customer success. FDEs at Mercor are builders first, embedding directly with enterprise clients to design and implement technical solutions that unlock the full value of Mercor’s platform while applying strong systems and product thinking where it matters. The work spans everything from architecting integrations and writing production-grade code to deploying scalable solutions in production environments, always tied closely to measurable business outcomes. You’ll collaborate with customer stakeholders and internal teams to deliver systems that directly shape how AI-powered human intelligence integrates into complex enterprises.

You will:

- Embed with enterprise customers to understand technical requirements and business goals.

- Architect and implement custom integrations, APIs, and workflows on top of Mercor’s platform.

- Deploy scalable solutions in client environments and drive successful launches and expansions.

- Build internal tools and reusable components that accelerate future de...

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