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# Platform Engineer

- **Company:** PHONICS, LLC
- **Location:** San Francisco, CA, United States
- **Contract:** Permanent contract
- **Skills:** Amazon Web Services, Microsoft Azure, Cloud Computing, Monitoring of Systems, Python (Programming Language), TypeScript, WebSocket, WebRTC, AI Infrastructure, Delivery Pipeline, Backend, Containerization, Kubernetes, Machine Learning Operations, Terraform, Stream Processing, Docker
- **Published:** September 4, 2026
- **Apply:** https://startup.jobs/platform-engineer-phonic-8402562

## About the Role

* 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

Nice To Have

 * Experience with real-time or streaming systems (WebSockets, WebRTC, or similar)
 * Familiarity with ML/AI infrastructure - model serving, GPU workloads, or inference optimization
 * Strong proficiency in TypeScript and Python
 * You are a former founder

## Description

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., * 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


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