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