Applied AI Engineer

This Applied AI Engineer role sits within an Applied AI Engineering team focused on helping enterprise organizations turn AI capabilities into reliable production systems. The work spans customer use cases and complex deployment environments, with close collaboration across customer engineering, product, research, security, and go-to-market teams.

The engineer designs, builds, evaluates, and deploys AI systems, moving them from use-case selection and architecture through prototyping, production launch, and scale. Day-to-day work includes writing and debugging code, building evaluation harnesses and integrations, diagnosing failures, and creating reusable architectures, tooling, and technical guidance. The role addresses models, agents, retrieval, tools, data, observability, latency, cost, safety, security, and governance.

Applicants should have a demonstrated record of designing, building, and delivering AI or machine-learning systems in enterprise environments, including taking systems from prototype to production. They must have made substantial personal contributions in code, architecture, evaluation, debugging, or production engineering, and be highly proficient in Python. They should also understand systematic AI evaluation using representative data, graders, production signals, and human judgment.