AI Engineer, Voice and Realtime

Role overview

Own the realtime AI interview pipeline behind live candidate conversations. The work covers audio ingestion, speech recognition, language-model decisions, speech output, turn-taking, vendor integrations, prompt design, and evaluation—while keeping responses fast enough to feel natural and respectful to the person being interviewed.

Responsibilities

- Build and operate the realtime interview worker, coordinating audio handling, speech-to-text, model calls, and conversational turn-taking within a defined latency budget. - Create prompts as versioned engineering artifacts and measure their behavior against a stable evaluation corpus. - Design scenarios, inspect transcripts, analyze failures, and establish quantitative evidence before releasing changes to the interviewer. - Maintain an abstraction layer around speech and model providers so vendors can change without forcing product-level rewrites. - Debug asynchronous and streaming systems in production and improve their reliability and observability. - Consider the candidate experience throughout the system, including clarity, timing, consistency, and fairness of the interaction.

Requirements

- Strong Python skills and experience shipping a production system that calls a language model, beyond notebook experimentation. - Practical experience with asynchronous programming, streaming data, and the debugging challenges those systems create. - A measurement-oriented approach to AI quality: you investigate failures systematically and use evidence to support changes. - Ability to work across prompts, application code, vendor integrations, and evaluation tooling. - Careful judgment about the people affected by automated interviews and the quality of their experience.

Nice to have

- Experience with WebRTC, LiveKit, or another realtime audio platform. - Previous work running model evaluations, A/B comparisons, transcript analysis, or other structured experiments on AI output.