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Software Engineer

  • Posted 5 hours ago
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Job 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.

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About Company

Job ID: 151863923

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