Senior DevOps Analyst

The Senior DevOps Analyst is responsible for leading the strategy, implementation, and continuous improvement of the organization’s DevOps platforms, infrastructure, leveraging AI functionality to increase productivity, and engineering toolsets. This role owns the DevOps roadmap, partnering with leadership to prioritize initiatives, evaluate emerging technologies, and drive adoption of modern software delivery practices across the enterprise.

Working closely with IT and business teams, this position designs and implements secure, scalable solutions including CI/CD pipelines, source control platforms, infrastructure automation, deployment orchestration, and developer tooling. The role helps teams automate processes, improve delivery efficiency, and adopt DevOps best practices.

A strong focus on security is essential, ensuring DevOps platforms, processes, and automation solutions align with enterprise security standards and secure-by-design principles. The role also contributes to governance and SDLC practices for emerging technologies, including AI-assisted development and AI-enabled solutions.

Core Responsibilities

Note: This is not an all-inclusive listing.

• DevOps strategy and roadmap: Lead DevOps best practices, maintain the DevOps roadmap, and help development teams mature their use of modern development tools and processes.

• Azure DevOps and GitHub enablement: Support and maintain Azure DevOps tools, automations, pipelines, and related processes. Help development groups establish repositories, adopt GitHub, and improve their development workflows.

• CI/CD and automation: Design, implement, and maintain CI/CD pipelines that enable reliable application deployment. Identify opportunities to automate development, testing, deployment, and operational processes.

• AI and emerging technology adoption: Evaluate and integrate emerging technologies in AI, automation, and DevOps to improve system capabilities and developer productivity. Partner with product and development teams to responsibly leverage AI functionality in development processes and production systems.

• AI agent platform, SDLC, and governance: Help establish and lead the lifecycle for AI agents, including platform ownership, SDLC practices, standards, security, compliance, and governance for users developing and deploying AI agents.

• Observability and operational reliability: Ensure systems are supported by appropriate logging, monitoring, and alerting practices, including solutions tailored to AI-enabled and distributed systems.

Behavioral Competencies

(Note: These are in addition to MGE’s Core Competencies)

• Manages Complexity - Navigates sophisticated technical environments and ambiguous AI challenges effectively.

• Drives Results - Consistently delivers high-quality, scalable solutions in fast-paced environments.

• Collaborates - Builds strong partnerships across engineering, data science, and business teams.

• Instills Trust - Gains credibility through technical expertise and reliable execution.

• Strategic Mindset - Anticipates future AI/technology trends and aligns solutions with long-term objectives.

• Advanced proficiency in cloud platforms (Azure)

• Strong experience with CI/CD tools (Azure Pipelines, GitHub Actions, etc.)

• Experience with AI-assisted development tooling (GitHub Copilot)

• Experience with AI frameworks (Copilot Studio)

• Knowledge of LLMs, agent frameworks, and prompt orchestration

• Proficiency in infrastructure as code (Terraform)

• Strong scripting/programming skills (PowerShell, Python, etc.)

• Advanced knowledge in DevSecOps and implementing secure SDLC practices and tools (GitHub Advanced Security, SonarQube, etc.)

Education

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field required

• Relevant certifications preferred (e.g., Microsoft Certified DevOps Engineer Expert, AI/ML certifications)

Experience

• 7+ years of experience in DevOps

• 2+ years of experience supporting AI systems in production environments

• Demonstrated experience with agent-based systems, LLM deployment, or advanced automation frameworks preferred