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)
