Composio provides a shared learning layer for AI agents to accumulate and share practical skills via integrations, handling multi-agent coordination, enterprise authentication, and scalable request processing across AI frameworks.
ABOUT COMPOSIO 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 https://lsvp.com/stories/investing-in-composio-building-the-backbone-of-ai-agent-intelligence/ with some incredible angels like Guillermo Rauch (CEO of Vercel), Dharmesh Shah (CTO of Hubspot), Gokul Rajaram. Beginning of this year we 3x'd our ARR, our customers range from your friends in the YC batch to Wabi, Glean, Zoom and many more. WHAT YOU'LL WORK ON - Build Automation Frameworks & Testing Infrastructure – Design, develop, and own automation frameworks, reusable test utilities, and quality tooling that enable scalable testing, validation, and release confidence across Composio's integrations, connectors, and agent workflows. - Validate Complex Integration Workflows – Design and execute test scenarios for critical integration workflows across internal and external systems, covering APIs, contracts, compatibility, authentication, webhooks, retries, idempotency, asynchronous workflows, and third-party dependencies. Identify edge cases and ensure reliable system behavior. - Enable Automation-Driven Quality Signoff – Build and maintain automated test suites, quality gates, and CI/CD checks that provide release confidence through functional, API, integration, contract, and regression testing. Analyse quality signals and engineering metrics to identify risks, prevent regressions, and support data-driven release decisions. - Build AI-Powered Quality Systems – Build AI-powered validation systems, agents, and automated workflows that help validate integrations, detect regressions, investigate failures, and scale quality across rapidly evolving products. - Improve Testing Strategy & Quality Practices – Contribute to testing approaches across integration, API, contract, and end-to-end layers. Improve test coverage, establish effective testing patterns, and strengthen validation practices across the engineering lifecycle. - Improve Reliability of AI-Native Products – Develop testing and evaluation approaches for AI-powered workflows, tool-calling agents, and other systems where outputs may vary between executions. Help measure quality, identify gaps, and improve confidence in AI-driven experiences. - Improve Production Quality & Reliability – Investigate production issues, contribute to root-cause analysis, enhance test observability, and implement preventive improvements that increase system reliability and platform stability. - Raise the Engineering Quality Bar – Partner with engineers to improve testability, provide input on design decisions, apply quality best practices, and help teams build reliable, testable systems. MUST HAVES AUTOMATION & QUALITY ENGINEERING - You build automation frameworks, quality platforms, and developer tooling that engineers rely on. - You write clean, maintainable automation and validation code, and understand how to apply the right quality strategy across API, integration, contract, and end-to-end layers. - You care about quality outcomes, CI/CD quality gates, release confidence, and reducing flaky tests—not just test execution. COMPLEX SYSTEMS & INTEGRATIONS - You can reason about API behavior, authentication, retries, idempotency, eventual consistency, and distributed systems. - You have experience testing, validating, and debugging integration-heavy systems involving multiple services and external dependencies. - You use logs, traces, metrics, and production signals to investigate failures and improve system reliability. AI-NATIVE - You actively use AI to accelerate testing, debugging, automation, or engineering workflows—with validation and critical thinking, not blind trust. - You understand AI agents, MCP/tool-calling systems, and LLM-powered workflows, and can think about evaluating and validating non-deterministic systems. PRODUCT JUDGEMENT - You make risk-based engineering decisions by balancing customer impact, reliability, delivery speed, and validation depth. - You understand user workflows and business impact, prioritize the highest-risk areas, and focus engineering effort where it creates the most customer confidence. OWNERSHIP & COLLABORATION - You take ownership of issues, drive them to resolution, and continuously improve quality outcomes. - You communicate clearly, explain technical trade-offs, and collaborate effectively across engineering teams. - You proactively learn, seek context, and independently solve ambiguous problems in a fast-moving environment.