AI Platform Operations Engineer

AI Platform Operations Engineer

Experience

Required:

Min 3 Years

Full-Time Job

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.

• 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.

• 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.

• Experience with AI Gateway solutions (Azure APIM AI Gateway or similar).
• Knowledge of Prompt Flow, AI evaluations, and model benchmarking frameworks.
• Experience with Lang Chain, Lang Graph, Semantic Kernel, or Auto Gen.
• Exposure to MLOps, CI/CD pipelines, Git Hub Actions, and Azure Dev Ops.
• 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 Fin Ops practices for AI workloads.

• 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 Gen
  2.
• Strong incident/problem management, stakeholder coordination, runbook preparation and knowledge-transfer skills.

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.

• 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.