Product Engineer

Location: Remote (North America) or Austin, TX

Employment Type: Full-time (no contractors)

Department: Engineering

About Hamming AI

Hamming builds three products for voice and chat AI agents: testing/simulation to validate behavior before launch; red-teaming to probe for prompt injection, jailbreaks, PII leakage, and policy violations; and production monitoring/observability to detect failures in live conversations and turn them into regression tests.

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.

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What you’ll do

• Own product features end-to-end: spec → prototype → ship → iterate, across frontend and backend.

• Work closely with customers: onboard new accounts, run weekly check-ins, and act as a high-agency partner to drive adoption and outcomes.

• Build core customer workflows for voice-agent QA: test creation, scenario management, evaluation results, analytics, debugging, and triage.

• Turn messy, high-dimensional data (calls, transcripts, tool events, traces, eval outputs) into product experiences that are obvious and actionable.

• Partner with customers to understand their reliability pain, then translate it into shipped product with measurable outcomes.

• Tighten the product loop: instrumentation, funnels, and feedback so we know what’s working and what’s not.

• Maintain high engineering velocity while keeping craftsmanship: clean APIs, strong abstractions, and excellent UI polish.

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

• Experience building analytics-heavy products (dashboards, event pipelines, debugging tools).

• Familiarity with LLM apps, evals, tool calling, or prompt/guardrail systems.

• Experience with real-time systems, telecom/voice, or high-concurrency workflows.

• Strong UI craft: interaction design, information architecture, and performance tuning.

Interesting problems you’ll touch

• Debugging workflows for voice agents: call timelines, transcripts, tool calls, traces, and “what changed?” diffs.

• Test authoring that scales: scenario libraries, parameterization, coverage, and regression packs.

• Evaluation UX: turning model-graded / heuristic / human feedback into trustworthy signals and action items.

• Analytics that matter: reliability metrics customers can run their business on.

• Enterprise readiness in-product: RBAC, audit trails, data retention, and environment/region controls.

   

Our stack

• App: Next.js, TypeScript, Tailwind

• AI: OpenAI, Anthropic, STT/TTS providers

• Realtime/Orchestration: LiveKit, Pipecat/Daily, Temporal

• Infra/DB: AWS, k8s, PostgreSQL, Redis, Terraform

• Observability: OpenTelemetry, SigNoz

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 [email protected] 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.