Senior AI Platform Operations Engineer

AI Platform Reliability and Operations • Administer and operate the AI platform to ensure availability, performance, and resilience across environments, integrations, and supporting infrastructure. • Monitor platform health using dashboards, logs, metrics, and alerts, and coordinate incident and service restoration activities. • Lead operational triage, escalation coordination, and post-incident reviews to strengthen services stability and resilience. • Track and report on service reliability indicators, incident trends, and operational performance.

AI Platform Enablement & Production Readiness • Enable approved AI use cases into production by ensuring: o Environment readiness, o Dependency validation, o Completion of operational readiness checklists, o Structured service transition activities • Support platform lifecycle management through: o Release coordination, o Change readiness validation, o Maintenance and capacity planning. • Ensure AI platform changes meet defined operational and control readiness criteria prior to release

Observability, Automation & AI Ops • Implement and maintain observability capabilities, including telemetry, logging, metrics, and traces required for enterprise AI operations. • Analyze operational data to identify anomalies, recurring issues, root-cause patterns. • Implement AI Ops use cases such as: o Alert correlation, o Anomaly detection, o Root-cause support, o Forecasting and predictive insights, o Automation of repetitive operational tasks. • Continuously improve operational efficiency through targeted automation and process optimization.

Governance, Risk, & Control Execution • Execute governance controls for AI solutions, including: o Usage and access controls, o Data privacy considerations, o Auditability and traceability, o Human oversight requirements • Ensure operational practices align with enterprise security policies, risk controls, and compliance requirements. • Maintain documentation and evidence required for audit, governance reviews, production readiness checkpoints, and control validation. • Identify control gaps and escalate risks appropriately to relevant governance and risk stakeholders.

AI Asset Visibility & Operational Integrity • Maintain operational visibility of AI platform assets required for monitoring, support, and cost alignment. • Validate asset ownership, relationships, and lifecycle status in collaboration with application and platform owners. • Support ongoing audits to ensure AI assets and associated cost attribution remain accurate and current.