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Phonic is a product and research lab building the most realistic, human-like voice AI conversations. The company has re-architected the entire stack—from models to product—to create voice agents that understand context, respond emotionally, and perform complex agentic tasks with frontier intelligence. Customers include companies building voice-native AI products in customer support, healthcare, logistics, and recruiting. Phonic has raised over $30M from tier-1 VCs and is led by top-tier AI researchers, international olympiad medalists, and former founders.
As a Member of Technical Staff, you'll own problems end-to-end across the full range of voice AI infrastructure: platform and infrastructure engineering, backend services and APIs, product surfaces, and applied research. You'll move fluidly between layers of the stack as the company needs problems solved, taking ownership from architecture and design through production and iteration. You'll partner directly with research and ML teams to translate frontier voice AI capabilities into reliable, production-grade systems. You'll help set technical standards and practices while the team is still small enough for individual contributions to matter significantly.
You should have a bachelor's degree (or higher) in Computer Science from a top university and a proven track record shipping production systems you're proud of. You need genuine interest and demonstrated ability working across the full stack—not confined to one layer. Strong fundamentals matter: clean, testable, maintainable code even when moving fast. You should have full-stack fluency with frontend, backend, infrastructure, and the integration points between them, or be demonstrably fast at picking up new stacks. An ownership mindset is essential: you move problems from ambiguous to shipped without needing fully-scoped specs. You ship, learn, and iterate quickly rather than over-planning, thrive with real scope and minimal oversight, and are comfortable being opinionated. You use modern AI tooling—coding agents, LLM APIs—as a natural extension of how you build.
Nice-to-have experience includes real-time or streaming systems (WebSockets, WebRTC, audio/media pipelines), early-stage startup experience where you helped set technical standards, familiarity with voice, telephony, or conversational AI products, or a background as a founder or technical lead.
