People In AI is an early-stage AI infrastructure startup focused on solving challenges in generative AI. They are seeking a Principal AI Engineer to help build reliable and debuggable production systems while influencing technical direction and supporting high-impact decisions.
Responsibilities:
- Help solve the reliability, observability, and remediation gaps holding back production GenAI
- Build the trust layer around LLM, RAG, and agentic systems
- Enable engineers to understand AI behavior, diagnose failures, and apply verified fixes
- Focus on systems, evaluation, and feedback loops rather than model training
- Shape architecture for GenAI evaluation, tracing, and remediation systems
- Advise on real-world behavior of LLM, RAG, and agentic workflows
- Design approaches to diagnosing AI failures and guiding engineers toward fixes
- Influence platform direction through deep applied AI expertise
- Support high-impact technical decisions across the company
Requirements:
- Engineering experience with deep exposure to applied AI systems
- Hands-on experience shipping LLM, RAG, or agent-based systems into production
- Strong systems thinking and architectural judgment
- Familiarity with evaluation frameworks, guardrails, or AI reliability patterns
- Comfort operating in ambiguity and shaping direction early
- Ability to communicate complex AI tradeoffs clearly to engineers and leaders