Senior / Staff+ Software Engineer, Voice Platform

Anthropic•Seattle, WA

18h•Hybrid

About The Position

Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems. We're building the infrastructure that lets people talk to Claude—real-time, bidirectional voice conversations that feel natural, responsive, and safe. This is foundational work for how millions of people will interact with AI. The Voice Platform team designs and operates the serving systems, streaming pipelines, and APIs that bring Anthropic's audio models from research into production across Claude.ai, our mobile apps, and the Anthropic API. You'll work at the intersection of real-time media, low-latency inference, and distributed systems—building infrastructure where every millisecond of latency is felt by the user. We partner closely with the Audio research team, who train the speech understanding and generation models, and with product teams shipping voice experiences to users. Your job is to make those models fast, reliable, and delightful to talk to at scale.

Requirements

Have 6+ years of experience building distributed systems, real-time infrastructure, or platform services at scale
Have shipped production systems where latency is measured in tens of milliseconds and users notice when you miss
Are comfortable working across the stack—from transport protocols and serving infrastructure up to the APIs product teams build on
Are results-oriented, with a bias toward flexibility and impact
Pick up slack, even if it goes outside your job description
Enjoy pair programming (we love to pair!)
Care about the societal impacts of voice AI and want to help shape how these systems are developed responsibly
Are comfortable with ambiguity—voice is a fast-moving space, and you'll help define the architecture as we learn what works

Nice To Haves

Real-time media protocols and stacks: WebRTC, RTP, gRPC bidirectional streaming, or WebSockets at scale
Audio engineering fundamentals: codecs (Opus, AAC), voice activity detection, echo cancellation, jitter buffering, or audio DSP
Low-latency ML inference serving, streaming model outputs, or GPU-based serving infrastructure
Telephony, live streaming, video conferencing, or voice assistant platforms
Mobile audio pipelines on iOS (AVAudioEngine, AudioUnits) or Android (Oboe, AAudio)
Working alongside ML researchers to productionize models—speech experience is a plus but not required

Responsibilities

Design and build the real-time streaming infrastructure that powers voice conversations with Claude—ingesting microphone audio, orchestrating model inference, and streaming synthesized speech back with minimal latency
Build low-latency serving systems for speech models, optimizing time-to-first-audio and end-to-end conversational responsiveness
Develop the public and internal APIs that expose voice capabilities to Claude.ai, mobile clients, and third-party developers
Own the audio transport layer—codecs, jitter buffers, adaptive bitrate, packet loss recovery—so conversations stay smooth across unreliable networks
Build observability and quality-measurement systems for voice: latency distributions, audio quality metrics, interruption handling, and turn-taking accuracy
Partner with Audio research to move new model architectures from experiment to production, and feed real-world performance data back into research
Collaborate with mobile and product engineering on client-side audio capture, playback, and the end-to-end user experience