Artificial Intelligence Engineer

Strong systems depth across backend services, integrations, data flows, and application logic Evidence of building internal platforms or workflow systems, not just end-user AI features Clear judgment about deterministic versus model-driven system boundaries

Experience with human review, escalation, auditability, and operational safeguards Willingness to work closely with teams to understand real workflows, not just stated requirements built internal platforms, shared services, or workflow systems used by multiple teams designed connectors, integration patterns, tool contracts, or context layers built AI systems for enterprise operations, security-sensitive workflows, compliance-heavy domains, or internal business processes Practical daily use of LLMs as building tools