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Open nowPosted 339 days ago

Staff Backend Engineer

hamming ai5 open roles

Where
Austin
Work mode
Hybrid
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Your applicationOpen nowStaff Backend Engineerhamming ai · Austin

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  4. 14.6%14 days
  5. 34.1%30 days
This job: posted 339 days ago

The posting

Location: Remote (North America) or Austin, TX

Employment Type: Full-time (no contractors)

Department: Engineering

WHY NOW

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 https://devin.ai/customers/hamming

Ranked #1 Eng team https://www.linkedin.com/posts/andrew-d-churchill_sumanyu-ceo-at-hamming-ai-had-20x-the-output-activity-7354564854029901824-jSDP?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAh-eI0Bl3EbQhXGlnjcZ4TbyeByvoh32hg

OpenAI Dev Day 100billion token list https://www.linkedin.com/posts/sumanyusharma_openaidevday-activity-7381718141455859712-OPhA?utm_source=share&utm_medium=member_desktop&rcm=ACoAAAh-eI0Bl3EbQhXGlnjcZ4TbyeByvoh32hg

WHAT YOU’LL DO

- Own core services in TypeScript/Node.js and Python that orchestrate LiveKit, Temporal, STT/TTS, and LLM tooling for real-time voice agents.

- Scale 1 → N → 100×: take what works today and harden it for 10K parallel calls with 99.99% uptime. Turn human playbooks into productized systems.

- Harden pipelines for ingestion, evaluation, and analytics so telephony events, recordings, and outcomes propagate reliably across services.

- Level-up observability: deepen OpenTelemetry/SigNoz and trace-first practices to shrink mean-time-to-truth in prod.

- Prototype → test → prod: partner with product to ship new LLM-driven behaviors with clear success metrics, guardrails, and regressions blocked in CI.

- Infrastructure readiness: CI/CD, environment automation, incident response playbooks—customer conversations stay online.

YOU MIGHT BE A FIT IF YOU

- Have senior/staff experience running distributed backends with real-time/streaming constraints.

- Are fluent in TypeScript/Node.js and comfortable jumping into Python for ML/audio jobs.

- Know Temporal (or similar workflow engines), queues, Redis, and PostgreSQL.

- Have shipped production LLM apps and understand prompt/tool design, evals, and guardrail instrumentation.

- Operate cloud-native on AWS with Terraform; k8s doesn’t scare you.

- Are a power user of Cursor/Zed/Devin and were using code-gen before it was cool.

- Have intuition for what current-gen LLMs can/can’t do—and what tomorrow’s models will unlock.

- Think independently, grind with customers, and do whatever it takes—without dropping the quality bar.

- Bonus: built 0→1 real-time systems in Telecom/Networking, Autonomous Vehicles, or HFT; founded something; built AI voice apps.

INTERESTING PROBLEMS YOU’LL TOUCH

- Voice simulations that feel real: accents, overlapping speech, crosstalk, background noise, barge-ins.

- Massive concurrency: 10,000+ parallel calls with deterministic behavior and graceful degradation.

- Temporal-driven orchestration for long-running, interruptible call flows.

- Closed-loop reliability: turn prod failures into auto-generated tests and blocked deploys.

- Trace-everything culture: make “what happened?” a 30-second question, not a war room.

HOW WE WORK

- 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.

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 make AI voice agents reliable at scale, let’s talk.

Send a short note (links to work > resumes) and tell us about something reliability-critical you shipped: what broke, what you fixed, and how you knew it worked.

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