Staff Voice AI Engineer – Core Platform

As a Staff Voice AI Engineer – Core Platform you will:
Contribute to the design, development and implementation of the core Voice Platform (Audio Acquisition, Conversation Management, Speech Generation, integration with API and self-hosted Voice AI models, Voice Harness)
Partner with product managers to work with customers, understand their use cases and technology challenges, and build for their success
Build and deploy large Voice AI distributed systems at scale spanning multiple regions and datacenters
Build high-quality, clean, scalable and reusable code by enforcing best practices around software engineering architecture and processes (Code Reviews, Unit testing, etc.)
Contribute to the continuous improvement of the SRE practice by turning operational use cases into requirements for software tooling
Be a mentor for colleagues and help promote knowledge-sharing across Voice AI engineering disciplines
To be successful in this role you have:
Experience in leveraging or critically thinking about how to integrate AI into work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI’s potential impact on the function or industry.
8+ year of relevant industry experience
Hands-on experience building distributed Voice AI systems with a large operational scale
~4+ years building LLM-based applications (integrating models, not training)
6+ years of development experience with Python, Golang, Java, or similar languages.
2+ years of experience building agents (prompt engineering) and developing LLM-based experiences
Working experience operating highly available distributed workloads on Kubernetes following a DevOps approach.
Experience building software for compliance and security in regulated environments is considered an asset
A proven track record of architecting and shipping distributed Voice AI or voice platform systems (real-time audio, STT/TTS, telephony or WebRTC) at large operational scale
Critically thinking around AI integrations for work processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI's potential impact on the function or industry.
Experience building with AI tools such as Claude Code, Cursor, Windsurf

Employment type
Full-time

Work arrangement
Hybrid