Overview
ProdE forms org-wide codebase intelligence - helping teams plan, build, and ship the software the world runs on. We outscored DeepWiki by 15%, Google Code Wiki by 38%, and Claude Code by 40% on AI codebase documentation benchmarks.
Now we're building AI agents for one of the hardest problems in enterprise software: planning. The systems you build will reason about high-stakes decisions for billion-dollar enterprises, where being wrong is expensive and being right is transformative.
This is not a wrapper-around-an-API job. You'll write production-grade code that holds up at scale and design agents that work when reality gets messy.
What you'll do
- Design, build, and ship production AI agents for enterprise planning.
- Make deliberate architectural choices: planning loops, tool use, memory, multi-agent, human-in-the-loop - and know when not to use each.
- Write production-grade Python that scales and stays maintainable.
- Build supporting infrastructure: data pipelines, retrieval, evaluation harnesses.
- Iterate on reliability, accuracy, and cost.
What we're looking for
- 2+ years of professional software development.
- Strong Python with a track record of production code at scale, not just prototypes.
- Hands-on experience building AI agents, not just using them.
- Real understanding of where LLM-based agents excel and where they fail.
- Familiarity with ReAct, planning/reflection loops, tool use, multi-agent orchestration, RAG-augmented agents, and the tradeoffs.
- MongoDB: schema design, queries, production use.
Nice to have
- Agent frameworks (LangGraph, LlamaIndex, CrewAI, AutoGen) - and comfort without them.
- Background in planning, scheduling, optimization, or operations research.
- Evaluation and observability tooling for non-deterministic systems.
- Enterprise software exposure.
Who you'll work with
A small, senior team - the co-founders, every day. Abhishek (CEO) led AI Agents at Leena AI (YC S18) from $100K to $10M ARR. Nilesh (COO) was a Director at a Series B company and learned ML at CMU. Our mentor, advisor, and investor Mitz Banarjee backs Anthropic, SpaceX, xAI, Perplexity, Groq, Cerebras, and Figure - and helped take Workiva (NYSE: WK) from founding to IPO.
How we work
- Core team, real ownership, early-team ESOPs on the table.
- Remote-first. Gurugram preferred for occasional in-person.
Important
In your applications, highlight your best work - not something vibe-coded from a single prompt, but real ingenuity and product thinking on a hard problem.