Senior Software Engineer, Voice AI
About the role
This is a high-autonomy, high-agency position for a voice AI engineer who thrives at the intersection of real-time systems, conversational AI, and healthcare. You'll own the architecture and delivery of Natera's Voice AI platform — a production system handling thousands of patient calls daily that provides automated status, identity verification, billing support, and intelligent routing to human agents. You'll work across the full voice AI stack: telephony, speech-to-text, LLM orchestration, text-to-speech, and analytics — building agentic conversational systems that directly improve patient access to their genetic sing results.
Responsibilities
- Own the end-to-end voice AI architecture — from Twilio media streams through LLM orchestration to TTS output and call disposition
- Design and implement multi-agent systems using tool calling, agent handoffs, and shared conversation state for complex patient workflows
- Build and optimize real-time audio pipelines — WebSocket streaming, codec handling (mulaw/PCM), VAD configuration, and interruption management
- Architect analytics and observability infrastructure for voice-specific metrics: per-segment latency (STT/LLM/TTS), call efficacy, disposition accuracy, and ASR error rates
- Solve voice-specific challenges: turn-taking timing, silence detection thresholds, barge-in recovery, medical term recognition, and end-to-end latency optimization
- Integrate voice agents with internal services via secure authenticated APIs
- Drive platform reliability — eliminate single points of failure, implement multi-provider LLM failover, and design graceful degradation paths
- Collaborate with product and clinical operations to improve self-serve efficacy rates and reduce call escalations
- Mentor team members on voice AI best practices and contribute to architectural decisions
Requirements
5+ years of software engineering experience, with at least 2 years building production voice AI or conversational AI systems
Deep experience with voice AI pipelines — you understand the end-to-end flow from telephony through STT, LLM processing, TTS, and back to the caller, and you've solved real problems at each stage
Production experience with agentic architectures — multi-agent orchestration, tool calling, agent handoffs, memory/state management, and LLM-driven decision making in real-time conversation contexts
Strong understanding of voice-specific challenges: VAD tuning, turn-taking, interruption/barge-in handling, latency budgets, audio codec management, and the differences between voice and text-based AI
Hands-on experience with telephony systems — Twilio (media streams, SIP, IVR), or equivalent platforms with WebSocket-based audio streaming
Proficiency in TypeScript/Node.js with strong async programming patterns; experience with NestJS or similar frameworks
Experience with STT/TTS providers (Deepgram, OpenAI, ElevenLabs, Azure Speech) and understanding of ASR accuracy challenges (domain-specific vocabulary, noise handling)
Production experience with LLM APIs — OpenAI (especially Realtime API), Anthropic Claude, or equivalent; prompt engineering for conversational agents
High agency and autonomy — you don't wait for permission, detailed specs, or hand-holding. You unblock yourself, seek out the highest-impact work, and drive it to completion
Excellent communication — you can translate complex voice AI architecture decisions for product and clinical stakeholders
Qualifications
Preferred Experience in healthcare, biotech, or regulated environments (HIPAA, PHI handling, zero-retention architectures, BAA compliance)
AWS infrastructure experience — ECS Fargate, Lambda, DynamoDB, Bedrock, Kafka/MSK, API Gateway, CDK
Background in real-time systems: WebSocket lifecycle management, connection resilience, streaming protocols
Experience building analytics pipelines for voice/conversational metrics (call efficacy, disposition tracking, latency observability)
Familiarity with RAG architectures (vector stores, embedding models, chunking strategies) for knowledge-grounded voice agents
Track record of migrating or evaluating vendor platforms while maintaining production uptime
Experience with Datadog APM, LLM Observability, or equivalent monitoring for AI systems
Skills
Deep understanding of voice-specific challenges: VAD tuning, turn-taking, interruption/barge-in handling, latency budgets, audio codec management, and the differences between voice and text-based AI
Hands-on experience with telephony systems — Twilio (media streams, SIP, IVR), or equivalent platforms with WebSocket-based audio streaming
Proficiency in TypeScript/Node.js with strong async programming patterns; experience with NestJS or similar frameworks
Experience with STT/TTS providers (Deepgram, OpenAI, ElevenLabs, Azure Speech) and understanding of ASR accuracy challenges (domain-specific vocabulary, noise handling)
Production experience with LLM APIs — OpenAI (especially Realtime API), Anthropic Claude, or equivalent; prompt engineering for conversational agents
High agency and autonomy — you don't wait for permission, detailed specs, or hand-holding. You unblock yourself, seek out the highest-impact work, and drive it to completion
Excellent communication — you can translate complex voice AI architecture decisions for product and clinical stakeholders
Benefits
Competitive Benefits - Employee benefits include comprehensive medical, dental, vision, life and disability plans for eligible employees and their dependents. Additionally, Natera employees and their immediate families receive free sing in addition to fertility care benefits. Other benefits include pregnancy and baby bonding leave, 401k benefits, commuter benefits and much more. We also offer a generous employee referral program!
We also offer a generous employee referral program!
For more information, visit www.natera.com.