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.
Devin Case Study
Ranked #1 Eng team
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Why this role matters
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.
What you’ll own
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Technical direction across the stack - backend, frontend, and infra. You’ll decide what’s “good enough” today and what deserves to be rebuilt.
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Team leadership: unblock engineers, set clear priorities, run lightweight design reviews, and keep the team aligned without red tape.
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System reliability: make sure our platform stays fast, observable, and stable while traffic grows 100x.
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Hands-on delivery: contribute to key projects weekly — from new product experiments to hardening real-time systems.
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Cross-functional glue: keep product and operations connected so decisions flow and context isn’t lost.
What you’ll do day to day
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Write code (TypeScript, Python, or both) alongside your team.
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Review architecture and PRs - guide decisions without micromanaging.
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Help define sprint priorities and keep roadmaps tight and realistic.
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Pair with engineers when things break - not just to fix them, but to make sure they don’t break again.
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Run post-mortems that actually lead to better systems, not longer docs.
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Evaluate new tech (LLMs, infra tools, observability stacks) and decide what’s worth bringing in.
You might be a fit if you
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Have 6 - 10 years leading 3 - 6 engineer pods in high-availability, high-frequency deploy shops.
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Built and operated realtime/distributed systems (workflow engines, WebRTC/telephony, large fan-out queues).
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Still enjoy shipping code and debugging hairy issues yourself.
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Have strong fundamentals across backend, infra, and architecture, and can also talk product tradeoffs fluently.
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Can move comfortably between TypeScript/Node.js, Python, and cloud infra (AWS, Terraform, Kubernetes).
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Understand how to design LLM-powered systems that are testable, measurable, and resilient.
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Communicate clearly - direct, concise, and respectful. You default to writing things down.
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Care about outcomes more than process.
Bonus points if you’ve:
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Built AI products (especially voice or real-time systems).
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Operated at an early-stage startup before - and liked it.
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Have an instinct for how to turn chaos into repeatable systems.
How we work
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Outcomes over output: we adjust roadmaps when new data lands.
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Demo early and document decisions so context moves fast.
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Own incidents: lead the investigation, write crisp notes, land durable fixes.
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Direct, candid, respectful communication keeps remote teammates in lockstep with Austin HQ.