Principal, Agentic Engineering Systems

Principal, Agentic Engineering Systems with a PhD in Mathematics and 15+ years of experience in production AI/ML. This individual specializes in building self-improving engineering systems that ship PRs against real enterprise codebases, including personal agents that learn each engineer's context and expertise, and the harness that keeps them in bounds. They recently led an AI tooling team at a Big 4 professional services firm, building production LLM tooling on open-source agent/RAG components. They have designed autonomous engineering systems for real enterprise software workflows using channels like repos, PRs, CI, and Slack. The profile highlights the development of an "Agent Harness architecture" to manage authority boundaries, blast-radius scoring, multi-agent consensus, and human approval routing. Their background includes leading MLOps adoption across 30+ business units, driving $48M in annual data-cost reduction, and building production RAG and Slackbot systems for public sector and Fortune-scale telecom. They have strong ML roots in signal processing, frame theory, NLP, time-series, and applied math, with a US patent pending. The individual is seeking roles focused on building governed engineering-agent fleets, agentic SDLC platforms, internal AI infrastructure, or principal-architect positions. They prefer C2C/1099 contracts but are open to full-time or fractional arrangements.