Forward Deployed Research Engineer
Forward Deployed Research Engineer embedded with enterprise customers to turn large APIs into agent-usable tools, ship production code, build evals, and own accounts end-to-end at an AI infrastructure startup.
About the job
Responsibilities
- Own enterprise accounts end to end: discovery, spec, implementation, QA, release.
- Ship production code in our toolkit monorepo and customer SDKs: custom and composite tools, schema and scope changes, per-customer patches.
- Turn large enterprise APIs into agent-usable tool surfaces, and build the evals that prove the model picks the right tool.
- QA toolkits, and build the harnesses that make QA repeatable instead of artisanal.
- Run weekly customer syncs: the summaries, ETAs, and escalations that keep an engagement coherent.
- Operate per-customer tool-patching as self-service, not escalation.
- Dogfood Composio on your own workflows.
Requirements
- Applied integration engineering: ship production code, live in enterprise APIs and auth (OAuth 2.0, consent models, scope design, multi workspace tokens).
- Customer technical ownership: taken a named enterprise account from first call to live; turn vague asks into specs and push back when wrong.
- AI native: built with and for language models; treat the agent-tool interface as an open research problem.
- Taste for good developer experience.
- Explain complex ideas clearly under deadline.
- Build trust and admit what you don't know.
Nice-to-Haves
- Years of Python in production (TypeScript a plus).
- API platform, iPaaS, or integration-heavy background.
- Prior FDE / solutions-architect role selling to big tech.
- Frontier output: MCP servers, tool-use evals, agent-tooling writeups.
Skills
Python, TypeScript, Oauth 2.0, Enterprise Apis, Integration Engineering, Agent Tooling, Evals, API Design, Sdk Development
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