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Senior DevOps Analyst

Job in Madison, Dane County, Wisconsin, 53774, USA
Listing for: Madison Gas and Electric
Full Time position
Listed on 2026-05-16
Job specializations:
  • IT/Tech
    AI Engineer, Cloud Computing, Systems Engineer
Salary/Wage Range or Industry Benchmark: 60000 - 80000 USD Yearly USD 60000.00 80000.00 YEAR
Job Description & How to Apply Below

Position Purpose

Leads the design, implementation, and maturity of AI-enabled Dev Ops platforms, with a focus on Microsoft Copilot, Git Hub Copilot, AI agents, and intelligent automation. Partners with technology and business stakeholders to enable scalable adoption of AI-assisted development and automation. Serves as a technical platform leader and advisor, integrating AI tools and agent-based solutions into Azure Dev Ops workflows and software development practices.

Establishes standards, patterns, and best practices to ensure secure, reliable, and governed AI-enabled solutions while accelerating delivery through modern Dev Ops and continuous improvement.

Core Responsibilities

Note:

This is not an all-inclusive listing

  • Design, build, deploy, and operate AI agents and intelligent automation solutions, including LLM-powered and multi-agent systems.
  • Lead the adoption of Microsoft Copilot, Git Hub Copilot, and Copilot Studio to enable AI-assisted development and improve engineering productivity.
  • Serve as a technical advisor to Dev Ops, application, and platform teams on AI-enabled development, automation, and agent-based solutions.
  • Design and maintain Azure Dev Ops CI/CD pipelines supporting AI-assisted development, automated testing, and continuous delivery.
  • Partner with software engineering, enterprise architecture, and product teams to integrate AI-driven capabilities into application and platform solutions.
  • Architect and manage secure, scalable Azure infrastructure for AI workloads using infrastructure-as-code practices.
  • Establish and operationalize Dev Ops and MLOps practices, including versioning, monitoring, governance, and lifecycle management of AI systems.
  • Implement and maintain observability solutions (logging, metrics, tracing, and alerting) for distributed and AI-driven systems.
  • Define and enforce security, compliance, and governance standards across AI systems, pipelines, and cloud platforms.
  • Evaluate emerging AI and Dev Ops technologies to improve reliability, developer productivity, and operational efficiency.
  • Optimize scalability, performance, and cost for AI-enabled platforms and compute-intensive workloads.
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 and technology trends and aligns solutions with long-term objectives.
Skills
  • Strong experience building, operating, and enabling AI agents, intelligent automation, and AI-assisted development workflows.
  • Hands‑on experience with Microsoft Copilot, Git Hub Copilot, Copilot Studio, or similar AI‑assisted engineering tools.
  • Deep mastery of Azure Dev Ops and modern Dev Ops practices, including CI/CD, Git, Git Hub, infrastructure as code, automation, and platform reliability.
  • Expert-level experience within the Microsoft ecosystem, including Azure, Azure Dev Ops, Git Hub Enterprise, and Azure‑native services.
  • Strong understanding of LLM concepts, agent orchestration frameworks, and prompt engineering (e.g., Lang Chain, Auto Gen, CrewAI).
  • Experience operationalizing AI and ML systems, including deployment, monitoring, governance, and lifecycle management.
  • Expertise in infrastructure as code using Terraform, Bicep, ARM templates, or similar frameworks.
  • Advanced experience with containerization and orchestration technologies such as Docker and Kubernetes.
  • Strong programming and automation skills using Python, Power Shell, Bash, or similar languages.
  • Experience implementing observability solutions using Azure Monitor, Log Analytics, Application Insights, or equivalent tools.
  • Advanced Git usage, branching strategies, and pull request workflows.
  • Strong understanding of security, identity, and compliance considerations in cloud and AI-enabled environments.
  • Proven ability to lead, enable, and influence Dev Ops and AI…
Position Requirements
10+ Years work experience
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