Staff Backend Engineer

Hamming AI • Austin, TX

15h • Remote

About The Position

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. This role is looking for someone who can own reliability and scale across our LLM-enabled platform, shipping precise, outcome-driven improvements to high-availability systems.

Requirements

• 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.

Nice To Haves

• Built 0→1 real-time systems in Telecom/Networking, Autonomous Vehicles, or HFT
• Founded something
• Built AI voice apps

Responsibilities

• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed