Software Engineer (AI Agents)

## About the role 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.