Backend / Infra Engineer

**Location: Remote (North America) or Austin, TX** **Employment Type: Full-time (no contractors)** **Department: Engineering** ### **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)\ 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.