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Clera

Voice AI Engineer

San FranciscoFrom $72kfulltimemidAdded today

About this role

Join an AI-native insurtech startup building a real-time voice platform that automates insurance workflows. As a Voice AI Engineer, you'll own telephony infrastructure, ASR/TTS pipelines, and agent systems handling millions of production calls at scale.

What you'll do

  • Build and maintain real-time voice platform including call handling, ASR/TTS pipelines, and latency-sensitive audio processing
  • Develop telephony infrastructure using Twilio/SIP and agent/skills layers for live production calls
  • Drive reliability and latency improvements for high-volume voice systems in production
  • Instrument and monitor voice quality metrics, latency budgets, and failure modes across the platform
  • Own features end-to-end from design through production deployment and post-launch support
  • Collaborate on agentic systems including tools frameworks, guardrails, and production evals

What they're looking for

  • Real-time voice/telephony systems (Twilio, SIP, ASR/TTS)
  • TypeScript and Node.js for production backends
  • Distributed and event-driven system architecture
  • Production observability and monitoring (Datadog experience preferred)
  • Temporal workflow orchestration
  • PostgreSQL and AWS infrastructure
  • LLM integration and agentic AI systems
  • On-call incident response and latency budget management

Benefits

  • Salary up to $72,000 USD annually (based on experience and location)
  • Fully remote work across LATAM, Ukraine, or Portugal
  • High autonomy and ownership engineering culture
  • Direct customer interaction and product influence
  • AI-native development environment with Claude Code and Codex
  • Opportunity to shape emerging AI+insurance market
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Clera

Clera builds an agentic operating system that automates complex workflows and processes through AI agents, with a platform designed to simplify distributed infrastructure management for developers. The company is hiring Founding Engineers, Customer Engineers, and Product Engineers to develop both backend systems and user-facing interfaces across their AI automation products.

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Likely interview questions

  • Walk us through a production voice system you've built or optimized—what were the latency and reliability challenges?
  • How have you used Twilio or similar telephony platforms in a real-time context, and what integration complexities did you encounter?
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