AI Platform Operations Engineer

AI Platform Operations Engineer Experience Required: Min 3 Years Full-Time Job Role Summary Responsible for the operational management, governance, and support of enterprise AI platforms, ensuring secure, scalable, and cost-effective onboarding and operation of Generative AI and Agentic AI workloads on Microsoft Azure. 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 APIM 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.