Tech Lead, Systems Engineer, AI Engineer

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)

Devin Case Study

Ranked #1 Eng team

OpenAI Dev Day 100billion token list

We’re moving fast, shipping constantly, and need a tech lead who can guide the team without slowing it down
.

This isn’t a people-manager role hidden behind meetings. You’ll lead a team of five engineers
, make architecture calls, mentor others, and still ship meaningful code every week
. You’ll be in the middle of everything - from scaling our evaluation engine to making sure customers love the product.

• Technical direction across the stack - backend, frontend, and infra. You’ll decide what’s “good enough” today and what deserves to be rebuilt.

• Team leadership: unblock engineers, set clear priorities, run lightweight design reviews, and keep the team aligned without red tape.

• System reliability: make sure our platform stays fast, observable, and stable while traffic grows 100x.

• Hands-on delivery: contribute to key projects weekly — from new product experiments to hardening real-time systems.

• Cross-functional glue: keep product and operations connected so decisions flow and context isn’t lost.

• Write code (Type Script, Python, or both) alongside your team.

• Review architecture and PRs - guide decisions without micromanaging.

• Help define sprint priorities and keep roadmaps tight and realistic.

• Pair with engineers when things break - not just to fix them, but to make sure they don’t break again.

• Run post-mortems that actually lead to better systems, not longer docs.

• Evaluate new tech (LLMs, infra tools, observability stacks) and decide what’s worth bringing in.

• Have 6 - 10 years leading 3 - 6 engineer pods in high-availability, high-frequency deploy shops.

• Built and operated realtime/distributed systems (workflow engines, WebRTC/telephony, large fan-out queues).

• Still enjoy shipping code and debugging hairy issues yourself.

• Have strong fundamentals across backend, infra, and architecture
  , and can also talk product tradeoffs fluently.

• Can move comfortably between Type Script/Node.js, Python, and cloud infra (AWS, Terraform, Kubernetes).

• Understand how to design LLM-powered systems that are testable, measurable, and resilient.

• Communicate clearly - direct, concise, and respectful. You default to writing things down.

• Care about outcomes more than process.

Bonus points if you’ve:

• Built AI products (especially voice or real-time systems).

• Operated at an early-stage startup before - and liked it.

• Have an instinct for how to turn chaos into repeatable systems.

• Outcomes over output
  : we adjust roadmaps when new data lands.

• Demo early and document decisions so context moves fast.

• Own incidents
  : lead the investigation, write crisp notes, land durable fixes.

• Direct, candid, respectful communication keeps remote teammates in lockstep with Austin HQ.

• App
  :
  Next.js, Type Script, Tailwind

• AI
  :
  OpenAI, Anthropic, STT/TTS providers

• Realtime/Orchestration
  :
  Live Kit, Pipecat/Daily, Temporal

• Infra/DB
  : AWS, k8s, Postgre
  
  SQL, Redis, Terraform

• Observability
  :
  Open Telemetry, Sig Noz

If you want to lead a small, senior team that’s building the backbone of reliable voice AI
, we’d love to talk.

Send a short note (no formal cover letter needed) to careers — tell us about something you built that scaled fast and stayed reliable.