Staff Platform Engineer, Voice AI

Responsibilities

• Own the architecture and reliability of Together's real-time API layer — set the technical direction for WebSocket and HTTP streaming APIs powering STT and TTS at scale; establish the reliability bar (connection lifecycle, backpressure, graceful degradation, reconnection) that production voice agents depend on.
• Lead autoscaling architecture for latency-sensitive voice workloads — design and ship orchestration systems that handle bursty, real-time traffic across tens of thousands of GPUs; solve problems at the intersection of concurrent connection limits, streaming state, and hard latency ceilings.
• Define the voice API feature surface — make architectural calls on word-level alignment, real-time speaker diarization, audio format support (g711/mulaw, PCM, WebRTC), pronunciation controls, and multi-context WebSocket.
• Build the observability platform for voice infrastructure — design latency breakdown pipelines, audio quality signal collection, and customer-facing dashboards for production-quality operation.
• Own the multi-provider abstraction layer — architect the normalization layer across model partners (Cartesia, Deepgram, Rime, and others) that delivers consistent, provider-agnostic API behavior.
• Drive the interface between API and ML serving — partner with ML engineering leadership to define the contract between the API layer and the model serving stack, impacting end-to-end latency and reliability SLAs.
• Raise the bar for developer experience across the platform — lead API design reviews, shape documentation strategy, define integration patterns and cookbooks.
• Architect for the product surface that doesn't exist yet — build systems that become the foundation for multiple new voice products.

Requirements

• 8+ years of experience building large-scale, real-time distributed systems with clear ownership of systems carrying production traffic at meaningful scale.
• Deep expertise in real-time streaming infrastructure — WebSocket server architecture, SSE, bidirectional streaming, connection multiplexing, stateful protocol design.
• Expert-level TypeScript and Python, with strong proficiency in systems-level thinking; Rust experience is a meaningful advantage.
• Senior distributed systems judgment — load balancing, autoscaling, rate limiting, and traffic shaping for latency-sensitive workloads.
• Deep Kubernetes expertise — custom autoscalers, resource management, and health checking for stateful, streaming services.
• Strong technical leadership — set direction, influence across teams without authority, bring clarity to ambiguous problems.
• Sharp product intuition for developer platforms — opinions about API ergonomics, thinking from the developer's perspective, shipped tooling developers praised.
• Proven ability to operate with autonomy on high-ambiguity, high-stakes problems.
• Experience with audio and media protocols (WebRTC, g711, PCM encoding) is strongly preferred.
• Familiarity with ML model serving infrastructure and inference engines is a significant advantage.
• Full-stack experience (React, Next.js) for developer-facing tooling contributions is a plus.
• Bachelor's or Master's in Computer Science, Computer Engineering, or related field — or equivalent depth demonstrated through work.

Nice-to-Haves

• Rust experience
• Experience with audio and media protocols (WebRTC, g711, PCM encoding)
• Familiarity with ML model serving infrastructure
• Full-stack experience (React, Next.js)

Compensation & Benefits

• Competitive compensation, startup equity, health insurance and other competitive benefits.
• US base salary range: $220,000 - $280,000 + equity + benefits.