Lead AI Platform Engineer

• Lead the engineering configuration and operation of enterprise AI platforms to ensure availability performance resilience and scalability across environments integrations and supporting infrastructure.
• Define and implement platform engineering patterns standards reusable components and operational guardrails that support secure and reliable AI solution delivery.
• Provide technical leadership for platform triage incident resolution escalation coordination and post-incident reviews to strengthen service stability and resilience.
• Track and report on service reliability indicators incident trends engineering risks and operational performance improvements.

AI Platform Enablement Solution Readiness Production Readiness and Technical Delivery

• Lead technical enablement of approved AI use cases into non-production and production environments by ensuring environment readiness dependency validation release readiness operational supportability and service transition planning.
• Partner with architecture security cloud infrastructure delivery and application teams to translate solution requirements into secure supportable and scalable platform implementations.
• Guide platform lifecycle management through release coordination change readiness validation maintenance planning capacity planning and technical risk mitigation.
• Ensure AI platform changes meet defined engineering operational security and control readiness criteria prior to release.

Observability Automation and AI Ops Engineering

• Design implement and continuously improve observability capabilities including telemetry logging metrics traces dashboards and alerting required for enterprise AI operations.
• Lead automation initiatives using approved tools and practices to reduce manual effort improve reliability and standardize repeatable operational activities.
• Analyze operational data to identify anomalies recurring issues root-cause patterns performance bottlenecks and opportunities for proactive service improvement.
• Implement AI Ops use cases such as alert correlation anomaly detection forecasting root-cause support knowledge retrieval and automation of repetitive operational tasks.
• Mentor engineers on observability automation troubleshooting and service reliability practices.

Governance Risk and Control Engineering Execution

• Embed governance security privacy auditability traceability and human oversight requirements into AI platform engineering and operational practices.
• Ensure platform implementations align with enterprise security policies risk controls compliance requirements architecture standards and operational readiness expectations.
• Partner with security risk compliance architecture and data teams to assess implementation risks close control gaps and enable responsible deployment of AI capabilities.
• Maintain documentation and evidence required for audit governance reviews production readiness checkpoints and control validation.
• Identify technical and control risks recommend mitigation options and escalate appropriately to relevant governance and risk stakeholders.

AI Asset Visibility Platform Integrity Operational Integrity and Engineering Standards

• Maintain engineering and operational visibility of AI platform assets required for monitoring support ownership lifecycle management and cost alignment.
• Validate asset ownership relationships configuration integrity and lifecycle status in collaboration with application platform architecture and infrastructure owners.
• Establish and promote engineering standards reusable patterns documentation and technical practices that improve platform supportability and operational integrity.

• University degree in Computer Science Engineering Information Technology or a related field or equivalent practical experience.
• 7 years of experience in platform engineering site reliability engineering DevOps cloud operations enterprise IT operations or production platform support.
• Demonstrated experience leading technical delivery engineering standards production readiness incident response problem management service restoration and operational reporting for enterprise platforms.

Technical Expertise:

• Advanced experience with cloud platforms observability automation configuration management and integration patterns including Azure Automation runbooks Azure AI Copilot integrations AKS virtual networks App Service and supporting Azure services.
• Strong expertise with observability tools such as Azure Monitor Application Insights Log Analytics Grafana dashboards alerting and operational telemetry design.
• Strong experience with CI/CD automation and infrastructure-as-code tools such as Azure DevOps GitHub Actions Logic Apps Bicep Terraform Azure Policy Key Vault and related open-source technologies.
• Knowledge of integration and event-driven technologies such as API Management open-source API tools Service Bus Event Grid and Apache Kafka.
• Working knowledge of platform-supporting data and search services such as Elastic Azure AI Search Cosmos DB and related data platform capabilities.
• Knowledge of enterprise network edge security identity access management and related internal platforms such as DNA Fortinet and Akamai is an asset.

Additional Capabilities:

• Strong working knowledge of AI/ML operational concepts including model lifecycle support platform telemetry governance controls human-in-the-loop practices responsible AI considerations and production monitoring.
• Strong understanding of ITIL/ITSM processes including change release incident problem configuration service reporting and operational risk practices.
• Proven ability to provide technical leadership mentor engineers influence standards guide implementation decisions and coordinate complex cross-functional delivery.
• Analytical and structured thinker with advanced troubleshooting root-cause analysis prioritization risk assessment and continuous improvement skills.
• Strong service orientation professional maturity and the ability to collaborate effectively across operations engineering security risk data architecture and business teams.
• Experience creating technical documentation engineering patterns operational procedures support playbooks dashboards and user guidance materials.