About the Role
The AI Platform Operations Engineer is responsible for the operational management, governance, and support of enterprise AI platforms. This role ensures the secure, scalable, and cost-effective onboarding and operation of Generative AI and Agentic AI workloads on Microsoft Azure.
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Key Responsibilities
- Operate Azure AI platform services, including Azure AI Foundry / Azure OpenAI and associated platform-level services.
- Support onboarding of Nexus AI, GenAI and agentic workloads using approved landing-zone patterns, platform blueprints, governance gates, and release processes.
- Support AI gateway / LLM gateway and API Management exposure, including API connectivity, registration, and production-readiness checks.
- Assist use-case teams with environment readiness, identity/access, network/API connectivity, deployment pre-checks, and post-deployment verification.
- Ensure AI workloads and agents are onboarded with approved guardrails, content-safety controls, observability, quota controls, cost attribution, and use-case governance.
- Support prompt/model monitoring, evaluation awareness, and AI observability; help validate dashboards, alerts, and operational health indicators.
- Support integrations with MCP/agent interfaces, data products, event streams, and operational data stores where applicable.
- Track incidents, onboarding issues, risks, and dependencies; coordinate resolution with Microsoft, Client IT, CIS, Architecture, Data & AI, and use-case teams.
- Maintain onboarding checklists, AI operational procedures, troubleshooting guides, governance evidence, and knowledge-transfer/handover materials.
Must-Have Skills
- Minimum 3+ years of hands-on Microsoft Azure experience.
- Strong experience with Azure AI Foundry, Azure OpenAI, and Azure AI Services.
- Experience with Azure API Management (APIM) and API exposure patterns.
- Knowledge of Generative AI, Large Language Models (LLMs), RAG, and Agentic AI concepts.
- Experience implementing AI guardrails, content filtering, and Responsible AI controls.
- Familiarity with AI observability, monitoring, logging, and performance tracking.
- Experience with Azure Monitor, Application Insights, Log Analytics, and Azure Cost Management.
- Understanding of Azure security, RBAC, Managed Identities, Key Vault, and networking concepts.
- Strong troubleshooting, operational support, and stakeholder management skills.
Good-to-Have Skills
- Experience with AI Gateway solutions (Azure APIM AI Gateway or similar).
- Knowledge of Prompt Flow, AI evaluations, and model benchmarking frameworks.
- Experience with LangChain, LangGraph, Semantic Kernel, or AutoGen.
- Exposure to MLOps, 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 Azure OpenAI at enterprise scale.
- Knowledge of quota planning, token consumption analysis, and FinOps practices for AI workloads.
Required Experience & Skills
- 3-10 years hands-on Azure administration/operations experience, including support of production cloud environments.
- Operational knowledge of Azure AI Foundry / Azure OpenAI, GenAI workload patterns, and agentic application operations.
- Understanding of AI gateway/APIM, REST APIs, MCP awareness, guardrails, content safety, prompt/model monitoring, and evaluation concepts.
- Experience with Azure monitoring/observability services such as Azure Monitor, Log Analytics, and Application Insights.
- Working knowledge of identity, managed identities, RBAC, secrets management, private connectivity, security controls, quota management, and cost attribution.
- Operational familiarity with APIM, Azure Event Hubs, Application Insights, Cosmos DB, and ADLS Gen2.
- Strong incident/problem management, stakeholder coordination, runbook preparation, and knowledge-transfer skills.
Preferred Certifications
- Strongly preferred: Microsoft Azure Administrator Associate (AZ-104).
- Additional preferred certifications: Azure AI Engineer Associate (AI-102) and Azure Solutions Architect Expert (AZ-305).
- Google Cloud Associate Cloud Engineer is an advantage due to cross-cloud dependencies.
Key Deliverables
- AI/use-case onboarding checklist
- Platform monitoring and incident register
- Security/governance evidence inputs
- AI operational runbooks and troubleshooting guides
- Operational dependency records
- Knowledge-transfer and handover pack
