AI Platform Operations Engineer

The AI Platform Operations Engineer will play a critical role in managing and supporting enterprise AI platforms to enable secure, scalable, and cost-effective deployment of Generative AI and Agentic AI workloads on Microsoft Azure. This position requires collaboration with multiple teams to maintain operational excellence, enforce governance policies, and ensure smooth onboarding and monitoring of AI workloads in a cloud environment. The engineer will be responsible for the end-to-end lifecycle of AI platform services, focusing on compliance, observability, and performance within a dynamic and evolving AI ecosystem.

Key Responsibilities
Operate and manage Azure AI platform services such as Azure AI Foundry, Azure OpenAI, and related platform-level tools. Support the onboarding of Nexus AI, Generative AI, and agentic workloads by applying approved landing-zone patterns, platform blueprints, governance gates, and release processes. Oversee AI gateway and Large Language Model (LLM) gateway operations, including Azure API Management (APIM) exposure, API connectivity, registration, and production readiness validation. Assist use-case teams with environment preparation, identity and access management, network and API connectivity, deployment pre-checks, and post-deployment verification to ensure operational stability. Enforce compliance with AI guardrails, content safety controls, observability standards, quota management, cost attribution, and governance requirements. Support prompt and model monitoring, evaluation awareness, and AI observability by validating dashboards, alerts, and operational health indicators. Facilitate integrations with Microsoft Cloud Platform (MCP) agent interfaces, data products, event streams, and operational data stores as needed. Track and manage incidents, onboarding challenges, risks, and dependencies, coordinating resolution efforts across Microsoft, Client IT, CIS, Architecture, Data & AI, and use-case teams. Maintain comprehensive onboarding checklists, operational procedures, troubleshooting guides, governance documentation, and knowledge-transfer materials to ensure continuity and compliance.

Required Qualifications
Minimum of three years’ hands-on experience in Microsoft Azure administration and operations, including supporting production cloud environments. Strong expertise with Azure AI Foundry, Azure OpenAI, and Azure AI Services. Proficiency in Azure API Management (APIM) and API exposure patterns. Solid understanding of Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI concepts. Proven experience implementing AI guardrails, content filtering, and Responsible AI controls. Familiarity with AI observability, monitoring, logging, and performance tracking tools such as Azure Monitor, Application Insights, Log Analytics, and Azure Cost Management. Knowledge of Azure security fundamentals, including Role-Based Access Control (RBAC), Managed Identities, Key Vault, and networking concepts. Strong troubleshooting and operational support skills combined with effective stakeholder management. Operational knowledge of Azure Event Hubs, Cosmos DB, ADLS Gen2, and identity/secrets management. Experience in incident and problem management, runbook development, and knowledge-transfer processes.

Preferred Qualifications and Benefits
Experience with AI Gateway solutions such as Azure APIM AI Gateway or equivalent technologies. Familiarity with Prompt Flow, AI evaluation frameworks, and model benchmarking methodologies. Exposure to LangChain, LangGraph, Semantic Kernel, or AutoGen frameworks. Understanding of MLOps practices, CI/CD pipelines, GitHub Actions, and Azure DevOps. Knowledge of Microsoft Purview, AI governance, and compliance frameworks. Experience with vector databases, Azure AI Search, and RAG architectures. Familiarity with Kubernetes, Container Apps, or enterprise-scale Azure OpenAI deployments. Awareness of quota planning, token consumption analysis, and FinOps practices for AI workloads. Preferred certifications include Microsoft Azure Administrator Associate (AZ-104), Azure AI Engineer Associate (AI-102), and Azure Solutions Architect Expert (AZ-305). Google Cloud Associate Cloud Engineer certification is a plus due to cross-cloud dependencies.

This role offers the opportunity to work at the forefront of AI platform operations, ensuring the robust, compliant, and efficient deployment of advanced AI workloads within a leading cloud environment. Key deliverables include AI onboarding checklists, platform monitoring and incident registers, security and governance documentation, operational runbooks, troubleshooting guides, and comprehensive knowledge-transfer packages.