- Location
- Haryana, Gurugram
- Type
- Full-time
- Department
- Engineering
- Experience
- 2+ years
- Source
- Freshteam
Description
About the job
We form 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.
