AI/ML DevOps Engineer

Who We AreJoin our global Centre of Excellence as a subject matter expert (SME) for Agentic AI Services, collaborating with teams worldwide to drive innovation and excellence. As part of this central function, you will help shape, implement, and scale cutting-edge Agentic AI solutions across the organization and our clientsThe AI/ML DevOps Engineer is a highly skilled expert responsible for designing, automating, and optimizing robust MLOps and DevOps environments to enable scalable, secure, and high-performing AI/ML platforms and applications.

This individual translates complex business and data science requirements into reliable data, model training, and inference workflows; deploys and manages multi-cloud and on-premises AI systems; and implements leading CI/CD, monitoring, and automation practices. The role combines deep experience in infrastructure-as-code, pipeline orchestration, cloud deployment, and operationalizing machine learning with mentoring responsibilities for junior and mid-level engineers. The goal: foster a collaborative, innovative, and operationally excellent AI/ML engineering culture.

What You'll Be DoingCollaborate with data scientists, solution architects, and platform specialists to translate business needs into technical architectures— incorporating both conventional ML workloads and agentic AI built with Azure AI Foundry, Copilot Studio, and Power Platform (Power Automate, Power Apps). Design, build, and maintain CI/CD and MLOps pipelines that cover the full AI/ML lifecycle—data, model, code, and agent deployment—leveraging Azure DevOps, GitHub Actions, and orchestration tools for both cloud-native code and low-code agents.

Automate the validation, deployment, and management of AI agents and copilots, ensuring best practices for versioning, testing, rollback, privacy, and security are applied across Azure AI Foundry and Power Platform. Integrate deployment of Power Platform solutions (Power Virtual Agents, AI Copilots, Power Automate workflows) and ensure governance, monitoring, and seamless scaling for enterprise-grade adoption. Support advanced data and model pipelines: from ingestion and feature engineering to deployment and on-going monitoring using Azure Machine Learning, Azure Synapse, Data Factory, and other relevant tools.

Containerize, deploy, and orchestrate solutions—including custom ML services and Power Platform connectors—with Kubernetes (AKS), Docker, and Infrastructure-as-Code (Terraform, Bicep/ARM). Embed automated testing, governance policies (via Azure Policy and Microsoft Purview), and security controls (integrating with Microsoft Defender for Cloud, Azure Key Vault, etc. ) into all DevOps processes, including those for low-code agents. Handle release management, environment provisioning, and runbook preparation for hybrid and multi-cloud scenarios (Azure, AWS, GCP). Troubleshoot complex deployment and operational issues—whether arising from custom code, integrated APIs, or Power Platform components.

Ensure comprehensive documentation is created for pipelines, deployment standards, agent lifecycle management, and regulatory compliance. Mentor and guide junior DevOps engineers and Power Platform specialists; lead knowledge-sharing and drive a culture of innovation, automation, and operational excellence. Stay current on Microsoft agentic AI advances (Foundry, Copilot/Power Virtual Agents) and related DevOps/MLOps patterns, continuously improving toolchains, and championing adoption of new features. What You'll Be DoingBachelor’s degree or equivalent in Information Technology, Computer Science, Engineering, or a related field.

Minimum 5 years of experience in designing and supporting DevOps and MLOps workflows for AI/ML and agentic AI solutions on Azure, with multi-cloud familiarity. Expertise in DevOps/MLOps for AI agents and ML models deployed on Azure, including advanced use of Azure DevOps, Azure Pipelines, GitHub Actions, and ARM/Bicep templates. Strong hands-on experience with Azure AI Foundry, Copilot Studio, Power Platform (Power Automate) and their integration into enterprise automation and conversational AI solutions. Familiarity with agent lifecycle management, automated testing and governance for low-code/no-code apps, and scalable Power Platform deployment patterns.

Competence with containerization (Docker), orchestration (Kubernetes/AKS), and multi-cloud deployment (Azure, AWS, GCP). Ability to design, implement, and maintain secure, automated deployment pipelines integrating security, compliance, and monitoring requirements. Advanced scripting/programming (Python, PowerShell, etc. ) and infrastructure-as-code (Terraform, Bicep/ARM). Proficient in Agile practices, strong planning, analytical, troubleshooting, and communication skills. Able to mentor, coach, and influence DevOps best practices across traditional and low-code environments. Microsoft certifications preferred (Microsoft Certified: Azure AI Engineer Associate, Power Platform Solution Architect, DevOps Engineer Expert). DevOps and cloud certifications for Azure, AWS, or GCP preferred.

Certification in relevant scripting or programming languages is advantageous. Hands-on experience with deployment and lifecycle automation for Azure AI Foundry, Copilot Studio, and Power Platform solutions. Proven success implementing CI/CD, automated testing, and governance for both code-centric and low/no-code AI applications. Demonstrated ability to work with diverse teams spanning software engineering, data science, and citizen developers. Significant experience with Agile methodologies (SCRUM, KANBAN) and in managing operational support for production AI/ML systems and AI agents. Excellent command of both spoken and written English.