Lead AI Platform Engineer

Purpose of the Job:

The Lead AI Platform Engineer is accountable for technical leadership, engineering excellence, reliability, operability, and the controlled enablement of the organization’s enterprise AI platforms.

This role provides hands-on technical leadership across AI platform design, implementation, automation, observability, and production readiness. The incumbent ensures AI platform services and solutions are secure, resilient, observable, supportable, and compliant with enterprise standards for reliability, security, platform management, monitoring, incident coordination, and governance control enforcement.

The incumbent acts as a senior technical lead for platform engineering activities, guiding implementation decisions, establishing engineering patterns, mentoring team members, and partnering with cross-functional stakeholders to enable the safe and scalable adoption of AI across the enterprise.

Knowledge/Skill Requirements:

• 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.