Platform Engineer

About the role

ABOUT PHONIC

Phonic is the speech-to-speech model company. Our mission is to make speaking with agents delightful, and we believe that requires models that hear and answer in native audio. To make that possible in production, we work on every layer of the stack: data, pre-training, post-training, kernels, and infrastructure. We’ve raised over $30M from top-tier investors, including First Round, Lux Capital, and Felicis. Our models power voice agents on six continents for companies like Ashby, Maven AGI, and a Fortune 50 IT infrastructure company, handling everything from customer support and patient intake to recruiting interviews and dispatch.

ABOUT THE TEAM

We’re a small team of researchers and engineers from MIT, Stanford, CMU, MosaicML, Citadel, and Genesis Therapeutics, including former founders, an IMO medalist, and an International Linguistics Olympiad medalist. We work in person in San Francisco five days a week. Everyone here is unusually obsessed with our customers: we’ll happily spend hours perfecting the way our model reasons while it talks, or the way it makes a caller feel heard, going as deep into the stack as it takes.

THE ROLE

As a Platform Engineer at Phonic, you'll build the foundation that lets our engineering team move fast without breaking things. Real-time voice AI at our scale is unforgiving — latency is visible, reliability is everything, and our systems need to perform flawlessly across hundreds of thousands of mission-critical calls every day. You'll own the infrastructure, tooling, and deployment systems that make that possible, freeing our backend and research teams to focus on pushing the frontier.

WHAT YOU'LL DO

- Design and maintain the core infrastructure that powers Phonic's real-time voice AI platform - cloud infrastructure, deployment pipelines, and observability systems

- Build internal tooling and abstractions that improve engineering velocity across the team

- Own reliability and performance at scale - define SLOs, instrument monitoring, and lead incident response when things go wrong

- Partner closely with backend engineers and researchers to translate cutting-edge AI capabilities into production-ready systems

- Drive improvements to how we build, test, and ship software - reducing friction across the entire development lifecycle

WHAT YOU'LL BRING

- Strong experience with cloud infrastructure - GCP, AWS, or Azure - and containerized deployments (Docker, Kubernetes)

- Proficiency with infrastructure-as-code tooling (Terraform or equivalent)

- A track record of improving reliability and developer experience in high-throughput, latency-sensitive systems

- Ownership mindset: you don't wait to be asked and you see problems through to the end

- Comfort dropping below the abstraction layer - able to debug at the level of bits and bytes when it's called for

- Strong system design instincts - clean architecture, high availability, and as few moving parts as possible