Lead AI Platform Engineer

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.

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.

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.

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.

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.