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.
- 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.
Skills Required
- At least 3 years of hands-on Microsoft Azure administration or operations experience
- Production cloud environment support experience
- Experience with Azure AI Foundry, Azure OpenAI, and Azure AI Services
- Experience with Azure API Management and API exposure patterns
- Knowledge of Generative AI, 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, networking, private connectivity, and secrets management
- Strong troubleshooting, operational support, incident and problem management, and stakeholder coordination skills
- Operational familiarity with Azure Event Hubs, Cosmos DB, and ADLS Gen2
- Runbook preparation and knowledge-transfer experience
- Experience with AI Gateway solutions
- 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, or 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 AI FinOps practices
- Microsoft Azure Administrator Associate certification AZ-104
- Azure AI Engineer Associate certification AI-102
- Azure Solutions Architect Expert certification AZ-305
- Google Cloud Associate Cloud Engineer certification
Datamatics Technologies Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Datamatics Technologies and has not been reviewed or approved by Datamatics Technologies.
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Flexible Benefits — Feedback suggests flexible timings and work-from-home options are available in some roles. This flexibility is highlighted as part of the employment experience across certain postings and materials.
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Wellbeing & Lifestyle Benefits — Feedback suggests flexibility around time off and remote work supports work-life balance. These elements can help offset leaner cash components for some individuals.
Datamatics Technologies Insights
What We Do
Datamatics Technologies (DMT) was established in Dubai. We specialize in providing onsite and offshore professional services, covering the full spectrum of Data Analytics and Data Science domains. Our experience of working with diverse industry sectors such as Telecoms, Finance, Government and Manufacturing, across multiple regions enables us to engage and deliver for our clients with confidence. We can offer our full portfolio of services through resource augmentation, managed services, both on T&M or fixed price financial arrangements. Through our end-to-end managed services offering we enable our clients to cut down costs, increase profitability and focus on value addition to their core business activities. Our project and delivery management team are certified in Agile, PMI and ITIL to ensure the planning and execution are carried out using industry best practices. We are working with our clients across Middle East and Africa Region.
