AI Platform Operations Engineer

Datamatics Technologies; Riyadh; On-site; SAR 180,000 - 360,000; Full time

Job summary

Datamatics Technologies is seeking an AI Platform Operations Engineer to manage enterprise AI workloads on Microsoft Azure. You will operate Azure AI Foundry/OpenAI services, support onboarding of GenAI workloads, and ensure secure, scalable, and cost-efficient platform operations.

The role requires 3+ years of Azure experience, strong knowledge of APIM and AI governance, and a focus on observability, security, and incident management.

Qualifications

• 3+ years hands-on Microsoft Azure experience.
• Experience with Azure AI Foundry / Azure OpenAI.
• Experience with Azure API Management (APIM).
• Knowledge of Generative AI and LLM concepts.
• Experience implementing AI guardrails and content safety.
• Familiarity with AI observability and monitoring.
• Experience with Azure Monitor, Log Analytics, App Insights.
• Understanding of Azure security, RBAC, and Key Vault.
• Strong troubleshooting and stakeholder management.

Responsibilities

• Operate Azure AI platform services and related platform-level services.
• Onboard Nexus GenAI and agentic workloads using landing-zone patterns.
• Manage AI gateway and APIM exposure, including production readiness checks.
• Assist use-case teams with environment readiness and deployment verification.
• Ensure guardrails, observability, quota controls, and cost attribution.
• Support prompt/model monitoring and AI observability dashboards.
• Coordinate integrations with data products and event streams.
• Track incidents and risks; coordinate with Microsoft and client teams.
• Maintain onboarding checklists and governance runbooks.

Skills

Azure administration

Azure AI services

APIM

Generative AI & LLMs

AI guardrails

AI observability

Azure Monitor

RBAC & security

Networking concepts

Incident management

Job description

AI Platform Operations Engineer

Full-Time Job

Experience Required

Min 3 Years

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.

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.

AI Platform Operations Engineer

Full-Time Job

Experience Required

Min 3 Years

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.

• 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.