Software Engineer 3, AI Framework Integrations

AI frameworks like LangChain, LlamaIndex, and n8n are quickly becoming the default way developers build with AI — and MongoDB wants to be the data platform that shows up everywhere they build. As part of the AI Builders Experience (ABX) org, we're standing up a brand new engineering team in Gurugram to make that happen, and we're looking for Software Engineers to be among its founding members.

The team owns the connective layer between MongoDB and third-party AI frameworks, platforms, and tools — the integrations that let developers use MongoDB effectively with the AI stack they've already chosen. That means shipping into some of the fastest-moving open-source ecosystems in tech, working mostly in Python and TypeScript, and partnering with the Database Experience (DBX) org when an integration needs new driver, platform, or product capability underneath it.

This is a strong role for an engineer who wants to grow into the AI space with real ownership. You'll own well-scoped projects from design through release, work with fast-moving and sometimes unproven technologies, and get a clear view of how the ecosystem is evolving. Priorities shift as frameworks change and customer demand moves, so we're looking for engineers who are adaptable, ask good questions, and take pride in shipping. Much of your work will happen in public: sending pull requests to upstream repositories, working through external maintainer review cycles, and participating in developer communities as MongoDB.

You'll work closest with the engineers sitting next to you, pairing on hard problems, reviewing each other's code, and dividing up a broad portfolio, with senior engineers and your manager close at hand as you take on larger pieces of it.

MongoDB engineering teams pride themselves on building high-quality software and living our cultural values every day. We value intellectual curiosity, intellectual honesty, customer empathy, and building together in an environment that prioritizes collaboration over competition.

We are looking to speak to candidates who are based in Gurugram for our hybrid working model.

• 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