Implement production‑grade AI services and pipelines (batch and real‑time) with strong focus on reliability, performance, and operational excellence in the cloud
Execute, manage and support the packaging and deployment of models and solutions as scalable services (APIs, jobs, agents) with clear SLAs, monitoring, alerting, and runbooks.
Own complex problem resolution across environments, including production incidents related to AI systems.
Embed AI governance directly into engineering workflows, including: Security and access controls Data classification and handling Model risk management requirements Privacy and consent controls Responsible AI principles Auditability and regulatory traceability