Sr AI Platform/AgentOps Engineer(Azure)

Job highlights

• . AI platform experience: AI / ML,GenAI,LLM,Copilot,agent,or similar modern AI workloads. AI .
• Required Qualifications
• Minimum of 4-6 years of relevant experience or equivalent combination of education and experience in Enterprise Applications

Develops, maintains and manages enterprise application standards and systems, including database, network and hosting solutions. Drives the development of detailed configuration parameters, custom extensions, workflow and integration solutions. Coordinates with technical / engineering teams to ensure solutions are designed to operate in highly available and reliable environments.

Required Qualifications

• Overall experience: 6-10+ years
• AI platform experience: AI/ML, GenAI, LLM, Copilot, agent, or similar modern AI workloads.
• AI Platform Engineering
• Containers/Kubernetes - AI/GenAI Platforms - AgentOps - Observability Telemetry
• • 3+ years in AI Platform Engineering
  • Strong hands-on production operations experience
  • Practical experience administering AI/ML, GenAI or agent platforms
  • Experience supporting enterprise-scale environments with security, governance, monitoring and automation
  • Experience moving applications or agents through Sandbox Dev Test Production
  • Strong troubleshooting capability across platform, application, integration, identity and infrastructure layers
• Minimum of 4-6 years of relevant experience or equivalent combination of education and experience in Enterprise Applications.
• Good business English skills (Written and spoken).

AI Platform /AgentOps Engineer

Primary Accountability
Industrialize AI solutions and agents into secure, scalable, observable and supportable enterprise services.

Core Responsibilities

• AI Platform Engineering - Build and operate shared AI platform capabilities and services.
• Environment Management - Manage Sandbox, Dev, Test and Production environments with controlled promotion.
• CI/CD Release Automation - Automate build, validation, deployment, versioning and rollback.
• AgentOps Administration - Manage agent configuration, deployment, publishing, lifecycle and operational controls.
• AI FinOps / Cost Controls - Track model, agent, API and infrastructure consumption and establish cost visibility.
• Security Access Controls - Manage identity, secrets, connections, environment isolation and platform-level controls.
• Production Operations - Establish production readiness, operational runbooks, incident support and lifecycle management.
• Platform Automation - Reduce manual administration through reusable infrastructure, deployment and operational automation
• Own the operational foundation for enterprise AI by administering AI platforms, Foundry environments, Copilot Studio and other agent platforms , while providing CI/CD,

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.