Principal AI Engineer

Sits at the intersection of software engineering, AI/ML, and platform architecture. This is a hands-on position — writing production code, architecting AI services, building internal tooling, and mentoring engineers — measured by outcomes that outlast your direct involvement, not by process ownership.

What You'll Do

● Design and build the AI productization patterns the team uses to ship AI/ML features — service patterns, evaluation approaches, production-readiness bar

● Build reusable internal tooling: AI service scaffolding, evaluation/monitoring tooling, data infrastructure — built for team adoption, not hand-holding

● Define baseline AI agent governance (permissions, execution controls, human-in-the-loop) as the team scales its AI usage

● Champion AI-assisted development practices day to day — this is a “build with AI,” not “write policy about AI,” role

● Establish deployment patterns (containerization, IaC, CI/CD) reusable across the team's products

● Mentor engineers, with visible improvement in delivery consistency and design quality as the marker of success

Required

● 10+ years in software engineering / data science, with substantial recent hands-on AI/ML work

● Deep Python ecosystem expertise; experience deploying models to production cloud infrastructure

● Demonstrated experience building multi-tenant AI services and LLM integrations in production

● Track record on microservices architecture — decomposing monoliths, defining service contracts, owning CI/CD for distributed systems

● Hands-on with Docker, Terraform, and modern DevOps practice

● Working knowledge of AI/LLM security fundamentals (prompt injection, data boundary enforcement)

● Strong written/verbal English

Preferred

● AI/ML applied in consulting, advisory, or professional-services contexts

● Go or TypeScript proficiency

● OSS contributions or active technical-community involvement

● Experience with SOC2/ISO-aligned compliance frameworks (a plus, not central to this hire)