Member of Technical Staff, Enterprise Product
Composio
Listing collected from Composio's career site. NextChapter is independent of Composio.
San Francisco, CA · Posted July 2, 2026
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November 2026
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Rankings about engineering jobs
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Pay compared with the market
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Among software developers, AI is already used for some of the tasks. Measured exposure for software developers: 29% (some).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
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About the job
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 raised a $25M Series A from Lightspeed https://lsvp.com/stories/investing-in-composio-building-the-backbone-of-ai-agent-intelligence/ with angels like Guillermo Rauch (CEO of Vercel), Dharmesh Shah (CTO of Hubspot), and Gokul Rajaram. We've 3x'd our ARR this year, and our customers range from your friends in the YC batch to Wabi, Glean, Zoom and many more.
Enterprise Product sits where the hardest customer workflows become durable product. You will work directly with enterprise customers and FDE, turn ambiguous asks into product primitives, and ship the code that makes the next customer easier than the last.
WHAT YOU'LL WORK ON
1. Turn large enterprise APIs into agent-usable tool surfaces: tool granularity, composite tools, descriptions, scopes, auth, and evals.
2. Productize repeated FDE work into self-service patching, QA harnesses, deployment paths, admin controls, docs, and guardrails.
3. Make enterprise deployments repeatable across hosted, VPC, on-prem, regulated, and BYOK environments.
4. Build the product layer that lets Composio scale from bespoke enterprise engagements to repeatable enterprise motion.
WHAT YOU'LL DO
• Own enterprise product surfaces end to end: discovery, spec, design, implementation, QA, release, adoption, and iteration.
• Ship production code across toolkits, SDKs, auth and scope flows, admin surfaces, deployment tooling, and customer-facing enterprise features.
• Work with FDE, customers, and core engineering to convert field pain into crisp product requirements and shipped primitives.
• Build evals and QA loops that prove enterprise workflows are reliable, not just demo-ready.
• Write the specs, docs, launch notes, and customer-facing updates that make the work easy to adopt.
"MUST HAVES"
if you are very good, nothing is a must per se
• Product-minded engineer: you turn messy workflows into clean product, then ship the code.
• Enterprise integration depth: OAuth, consent, scopes, service accounts, webhooks, rate limits, and strange API behavior do not scare you.
• Customer ownership: you can take a named customer or product surface from first conversation to live usage.
• AI native: you have built with language models, built for language models, and have opinions on agents, MCP, evals, and tool choice.
• Systems judgment: you think in rollout paths, rollback paths, security exposure, version skew, and maintainability.
• Clear writer: your specs, docs, and customer updates earn trust under deadline.
OPTIONAL
• Python in production; TypeScript a plus.
• API platform, iPaaS, developer tools, infra, or integration-heavy background.
• Prior FDE, solutions architect, sales engineer, or enterprise product engineering role.
• Kubernetes, Helm, Temporal, Postgres, Replicated, cloud secret managers, or packaged self-hosted delivery.
• Security and compliance exposure: SOC 2, Vanta-style programs, questionnaires, CVE triage, or RCAs.