Platform Engineer

Phonic is a product and research lab focused on powering the most realistic, human-like voice AI conversations. We've re-thought the entire stack in pursuit of this goal, from models to product, to create voice agents that feel like they truly understand you, respond emotionally and perform agentic tasks with frontier intelligence.

Our team includes top-tier AI researchers, international olympiad medalists, and former founders.

Our customers include companies that are building voice-native AI products in industries such as customer support, healthcare, logistics, and recruiting. We have raised over $30M from tier 1 VCs.

Phonic has a very talent-dense and close-knit team. We collaborate with high trust and are constantly trying to improve how we work to deliver world-class research and product. Everyone takes ownership in what they do and they aren’t afraid to dive in headfirst into new problems.

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.

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

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

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

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

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

• 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

• A track record of driving performance at scale - pushing requests-per-second toward best-in-class efficiency

• 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