About the role

InCommon helps fast-growing companies hire exceptionally good talent in India and the US — recruitment, EOR, the whole employer stack. Over years of running that at scale, we've built up domain knowledge about what actually makes a hire work: what separates a resume that looks good from a candidate who performs, what predicts a rapid close vs. a stalled one, what a client says they want vs. what they actually respond to. We're now building a hiring intelligence system to encode that knowledge into the product itself — not just an ATS with some AI features bolted on.

We need someone to own the technical charter for this — architecture, roadmap, code quality, and execution — not join as a support engineer under someone else's spec. You'll work directly with the technical co-founder, but the expectation is that you run engineering, not wait for it to be run for you.

The product context

InCommon is building the hiring intelligence platform. Every hiring cycle generates structured data most companies throw away: why candidates got rejected, what made hiring managers say yes, what actually predicted a good hire. The AI-assisted layer today (scoring, drafting, flagging) is deliberately human-in-the-loop — it proposes, never acts — which means every data point in the system is backed by a real human decision, not a model guess.

That's what makes it possible to build real intelligence on top of it later, rather than just a better ATS.

You'd be one of the first people making the architecture calls that decide whether that second act is even possible.

What you'll own

Technical ownership





- Architecture and technical direction for the hiring-intelligence platform going forward
- Full ownership of features end-to-end — design, build, ship, maintain — without needing a detailed spec handed to you
- Make the build-vs-defer calls yourself and defend them

Product execution

- Turn loosely-defined product direction (from the founders, from client/recruiter feedback) into a working roadmap
- Ship independently; loop in the co-founder for direction, not for permission on every decision
- Maintain and extend the AI-assisted features (candidate scoring, drafting, flagging) within the existing design principle: AI proposes, humans decide — every automated capability keeps a human checkpoint

Engineering quality & scale

- Set the bar for code quality, testing, and how the codebase evolves as more people (eventually) touch it
- Decide what to build in-house vs. buy/integrate
- Own reliability of systems that recruiters and client hiring managers depend on daily

What you'll need

- 5+ years building and shipping production software, with real ownership of a system end-to-end (not just tickets from a backlog)
- Comfortable being the most senior technical person in the room day-to-day — this role does not come with a team to lean on initially
- Full-stack capability — you'll build across the stack, not just one layer
- Experience (or strong interest) working with LLMs in a production context: RAG, evals, agentic workflows — not just API calls
- Product sense — able to take an ambiguous problem ("recruiters spend too long triaging resumes") and turn it into a scoped, shippable feature
- Startup/small-team experience where you were the decision-maker on technical trade-offs, not just an executor

📌 Head of Engineering (Founding) (Pune)
🏢 InCommon
📍 Pune