Senior Cloud (Azure) Engineer

We are seeking a client-facing Senior Cloud (Azure) Engineer to join our dynamic Business Platform Team. You will be responsible for shaping new tool assessments (including AI-driven tooling and LLMOps/MLOps pipelines), establishing rigorous governance frameworks, defining best-practice patterns, and architecting critical project setups from the ground up.

If you have a strong background in Azure DevOps, hands-on experience integrating AI solutions and tools into enterprise workflows, and excel at guiding stakeholders through complex technical transformations, we want to hear from you.

Responsibilities

• Collaborate closely with clients to understand their business and AI adoption requirements, evaluate their maturity, and consult on Azure DevOps and AI integration best practices
• Serve as the technical subject matter expert during client workshops, discovery sessions, and project kickoff phases for both traditional cloud and AI-driven initiatives
• Design, architect, and bootstrap robust CI/CD pipelines, repository structures, and secure workspaces for critical client initiatives — specifically incorporating AI solutions, prompt engineering pipelines, and LLM integrations
• Standardize project onboarding processes to ensure rapid, scalable, and secure delivery environments
• Integrate modern AI tools, coding assistants (e.g., GitHub Copilot, Azure AI services), and AI-driven workflow automations into the engineering ecosystem
• Establish and enforce enterprise-grade governance models within Azure DevOps, including security policies, access control, auditing, and ethical/secure use guidelines for AI tools and models
• Monitor and optimize platform usage to ensure adherence to compliance standards, cost control, and data privacy
• Research, evaluate, and pilot emerging DevOps platforms, developer tooling, and AI-driven software development lifecycle (SDLC) solutions
• Define migration strategies, risk assessments, and adoption roadmaps for newly approved tools
• Develop and maintain reusable patterns, YAML pipeline templates, infrastructure-as-code (Terraform), and reference architectures tailored for AI and cloud workloads
• Document standards and mentor development teams on efficient, AI-augmented DevOps workflows
• Troubleshoot and trace complex issues across distributed systems to ensure platform reliability and performance

Requirements

• 3+ years of hands-on experience in DevOps engineering, cloud infrastructure, or software delivery automation, with a strong emphasis on Microsoft Azure
• Expertise in Azure DevOps Services/Server (Repos, Pipelines, Artifacts, Boards)
• Proficiency in designing and maintaining CI/CD pipelines for enterprise-grade delivery
• Skills in containerization and orchestration with Kubernetes
• Background in Infrastructure as Code (IaC) using Terraform
• Capability to troubleshoot and trace issues in distributed systems
• Understanding of governance and security practices, including Role-Based Access Control (RBAC), service connections, and compliance guardrails — especially around data governance in AI projects
• Proven track record of working closely with external clients, gathering requirements, presenting technical solutions, and managing stakeholder expectations
• Excellent verbal and written communication skills, with the ability to bridge the gap between technical, AI, and business stakeholders

Nice to have

• Microsoft Certified: DevOps Engineer Expert and/or Azure AI Engineer Associate certifications
• Experience working within a Business Platform, Internal Developer Platform (IDP), or MLOps-focused team
• Experience with GitHub Copilot and other AI-powered developer tooling
• Knowledge of Helm for Kubernetes package management
• Proficiency in Python scripting for automation and tooling
• Familiarity with GitOps workflows (Flux)