Build, test, and ship MongoDB integrations across a broad AI framework ecosystem that includes technologies like LangChain, LangGraph, LlamaIndex, n8n, and Mastra
Own well-scoped projects end to end on weekly-to-quarterly timelines, taking responsibility for the scope, schedule, and quality of your own work and communicating progress and trade-offs clearly
Solve day-to-day technical problems with growing independence, using the team's established patterns and past practice to guide your decisions, and seeking guidance on non-standard problems
Contribute to exploratory work on new frameworks: help evaluate an integration's feasibility, build a first working version of the piece you own, and share what you learn with the team
Contribute high-quality code upstream to repositories MongoDB doesn't own, following the team's contribution practices and maintaining a high standard of professionalism and courtesy through external maintainer review cycles
Work within and improve the team's engineering practices: CI/CD, automated testing across framework and server versions, version compatibility checks, and release steps. Suggest improvements where you see repeated friction
Help keep the integrations you work on healthy: monitor for upstream breaking changes, handle upgrades, triage incoming issues, and follow through after release
Coordinate with adjacent teams, including DBX, when your work depends on driver, platform, or product capability, and escalate cross-team dependencies and risks early rather than working around them
Collaborate with product management, product design, and other partners to understand what users need from an integration and how your work connects to the team's objectives
Write clear documentation, give useful code reviews, share what you know with teammates, and follow through on your commitments
Develop specialized knowledge of the Python or TypeScript AI builder ecosystems — frameworks, agent and retrieval patterns, vector search — and bring interesting developments back to the team