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Hamming AI · Hiring

Product Engineer

AustinHybridFull Time

Location: Remote (North America) or Austin, TX

Employment Type: Full-time (no contractors)

Department: Engineering

About Hamming AI

Hamming automates QA for voice AI agents. Everyone is building voice agents. We secure them. In fact, we invented this category. With one click, thousands of our agents call our customers’ agents across accents, background noise, and personalities—then we generate crisp bug reports and production-grade analytics. Reliability is the moat in voice AI, and that’s our whole job.

We are one of the fastest engineering teams in the world. We prod deploy 4x / day. I’m looking for someone who can own reliability and scale across our LLM-enabled platform, shipping precise, outcome-driven improvements to high-availability systems.

Sumanyu (CEO)

Previously: grew Citizen 4× and scaled an AI sales program to $100Ms/yr at Tesla.

Devin Case Study

Ranked #1 Eng team

OpenAI Dev Day 100billion token list

What you’ll do

You might be a fit if you

  1. Have 3+ years building customer-facing products in a high-velocity environment (startup experience a plus).

  2. Are fluent in TypeScript and comfortable across the stack (React/Next.js + Node services).

  3. Ship quickly but with discipline: you write clear code, strong tests where it matters, and avoid accidental complexity.

  4. Have strong product instincts: you can simplify complex workflows into crisp UX and make good tradeoffs under ambiguity.

  5. Love talking to users, diagnosing friction, and iterating until a feature feels “done.”

  6. Care about reliability: you build with observability, failure modes, and data correctness in mind.

  7. Communicate clearly: written specs, crisp PRs, and decisions that scale across a fast-moving team.

Bonus

Interesting problems you’ll touch

Our stack

Apply

If you want to build the product layer for reliable Voice AI, let’s talk.

Send a short note (links to work > resumes) to careers@hamming.ai and tell us about a product you shipped end-to-end: what you built, where it was painful, what tradeoffs you made, and how you knew it worked.

Interested in This Role?

Apply at Hamming AI

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