Member of Technical Staff - Research Engineer

sf on site Until 8/22/2026 First posted March 18, 2026 Last posted March 18, 2026
Job description

At Composio, we are building infrastructure that allows agents to communicate with the tools you use for work including Github, Gmail, Notion, Salesforce, etc. We are a small team of engineers wrangling problems from context to search, that help us provide the most capable bridge between your agents and your tools.

We raised a $25M Series A from Lightspeed with some incredible angels like Guillermo Rauch (CEO of Vercel), Dharmesh Shah (CTO of Hubspot), Gokul Rajaram. Beginning of this year we 3x our ARR, our customer range from your friends in the YC batch to Wabi, Glean, Zoom and many more.

What you'll do?

  • build large evals with real tool calling data, measuring where models suck in long horizon tool execution

  • work on search problems for finding semantically similar tools and cached tool execution paths and plans.

  • train large agentic harness systems to improve session accuracy with millions of real tool calls as baseline data

  • SFT on our agentic traces and RL models on top of our agentic harness and app sandboxes.

"Must haves"

if you are very good, nothing is a must per-se

  • research

    • you can independently execute against the research goals

    • you can prototype and test experiments very quickly

    • you can work with product and engineering teams to take research ideas to production in a matter of days

  • typist — you can write docs well and explain complex ideas clearly

  • human — you build trust and admit what you don’t know

About this role

Summary

Research and prototype systems for AI agent communication tool integration and improvement

Job title

Member of Technical Staff - Research Engineer

Experience level

none specified

Industry

software

Location requirements

remote work possible, based in sf or elsewhere

Salary

Not specified

Management role

No

Skills & keywords

Required skills

researchprototypeexperimentdocumentationcollaboration

Preferred skills

machine learningLLMsRLSFTtool use

Specializations

large evalssearchmachine learningsearch problemsLLMs
Locations

Structured locations inferred from the posting.

San Francisco, CA, USA

Remote City