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Composio

Forward Deployed Research Engineer

sffulltimemidAdded 1 month ago

About this role

Composio seeks a Forward Deployed Research Engineer to work directly with enterprise customers on the cutting edge of AI agent infrastructure. You'll transform complex APIs into agent-accessible tools, ship production code, and help define best practices for an emerging field—embedding with customers and turning research questions into deployed solutions.

What you'll do

  • Own enterprise accounts end-to-end from discovery through implementation and release
  • Ship production code for custom tools, schemas, and per-customer patches in the toolkit monorepo
  • Convert large enterprise APIs into agent-usable tool surfaces and build evaluation harnesses
  • Conduct weekly customer syncs, manage timelines, and handle escalations
  • Design tool granularity, scope, and descriptions to optimize model navigation
  • Build repeatable QA processes and enable self-service tool patching

What they're looking for

  • Production integration engineering and enterprise API expertise
  • OAuth 2.0 and authentication/scope design experience
  • Python or TypeScript proficiency
  • Large language model application development
  • Technical account ownership and customer communication
  • API platform or iPaaS background
  • Systems design under pressure
  • Clear technical writing and explanation
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Composio

Composio builds agent-to-tools infrastructure that enables AI agents to interact with external systems and APIs. The company is hiring AI engineers, deployment specialists, growth engineers, and customer-focused research engineers to expand its platform, improve production deployments, drive adoption, and work directly with enterprise customers.

View all jobs at Composio

Likely interview questions

  • Walk us through a time you took an enterprise API from discovery to production integration. How did you decide what to expose to users, and what trade-offs did you make?
  • Tell us about a complex OAuth or auth flow you've implemented. How did you handle edge cases around scopes, consent models, or multi-workspace tokens?