Applied AI Engineer

Interview Copilot AI builds a privacy-first desktop assistant that helps candidates perform at their best in live job interviews. The product combines live transcription and conversation context to deliver clear, résumé-aware guidance in real time. What you’ll own You will own applied AI systems that turn speech and interview context into useful, dependable product behavior. This is product engineering rather than foundation-model research. Key responsibilities • Build and improve LLM pipelines for question detection, context handling, and structured guidance. • Design prompts, structured outputs, evaluations, and quality feedback loops. • Integrate speech and transcription systems for low-latency live experiences. • Improve latency, reliability, privacy, and cost across AI-powered workflows. • Operate multi-provider AI integrations with sensible fallbacks and failure recovery. • Partner across product and engineering to turn ambiguous needs into measurable system behavior. • Add testing and observability that make AI quality and regressions visible. Required skills • Experience shipping production software that uses modern AI or language-model APIs. • Strong general software-engineering and debugging fundamentals. • Practical experience with prompting, evaluation, and structured model outputs. • Ability to reason about latency, reliability, and product quality. • Clear written communication and comfort working autonomously. Nice to have • Speech-to-text, audio, or transcription systems. • Multi-provider AI architecture and fallback strategies. • Real-time or streaming applications. • TypeScript, PostgreSQL, or Cloudflare Workers. • Experience building internal evaluation tools or datasets. Remote working This is a full-time, fully remote role. Applicants are welcome from anywhere in the world. The role suits someone who communicates clearly, documents decisions, and moves work forward independently. Hiring process The hiring process is conducted remotely through vi