Azure DevOps & GitHub Architect — Cloud & AI Delivery

Devopsroles

Seattle (WA)

Remote

USD 155,000 - 184,000

Full time

14 days+

A complete application in a minute

Tailored resume and cover letter, ready to send.

Get past ATS filters

Benefits offered by this job

Training and certifications

Global resources access

Career advisor

Job summary

Avanade, Seattle-based, seeks an Azure DevOps & GitHub Engineer/Architect at the manager level to lead the design and implementation of DevOps solutions using Azure DevOps, GitHub Enterprise, GitHub Copilot, and Azure technologies.

You will guide clients on AI-enabled engineering vision, adoption roadmaps, governance, and cost management while coaching teams on CI/CD, GitHub Actions, and cloud environments. Hands-on SDLC and platform engineering experience required.

Qualifications

7+ years of IT experience with strong hands-on cloud, GitHub, and DevOps expertise.
2+ years in a lead, architect, or senior technical role.
Proven experience designing and deploying cloud solutions at scale.
Strong hands-on experience with Azure DevOps, GitHub Actions, and/or Jenkins for end-to-end CI/CD pipelines.
Proficiency in scripting and automation using PowerShell, Bash, and/or Python.
Solid understanding of CI/CD, Git branching strategies, and release management.
Experience advising on DevOps best practices and aligning technical solutions to business objectives.
Experience guiding enterprise clients through GitHub Copilot adoption, enablement, governance, cost optimization, metrics, and value realization.
Familiarity with DevSecOps practices, including security scans, secrets management, and quality gates.
Experience with hybrid or multi-cloud environments and networking, such as VPNs or ExpressRoute.
Knowledge of reliability engineering principles, infrastructure performance tuning, and cost optimization.
Understanding of ITIL or ITSM processes supporting CI/CD toolchains.
Familiarity with compliance frameworks such as NIST, HIPAA, PCI, or ISO 27001.
Bachelor’s degree in computer science, engineering, or a related field, or equivalent professional experience.

Responsibilities

Define and lead Azure DevOps strategy aligned with enterprise and client objectives.
Lead GitHub and engineering transformation strategies aligned with client and enterprise objectives.
Serve as a trusted advisor to business and technology leaders on GitHub-powered AI adoption, AI-enabled SDLC practices, DevSecOps, and software engineering modernization.
Lead discovery sessions, assessments, workshops, and roadmap engagements with client stakeholders.
Champion modern software engineering, DevOps, DevSecOps, and platform engineering practices across engagements.
Design and implement GitHub Enterprise architectures, governance models, repository strategies, and operating frameworks.
Architect and optimize GitHub Actions workflows, CI/CD platforms, and software delivery pipelines.
Lead migration initiatives from Azure DevOps, Jenkins, Bitbucket, GitLab, and legacy toolchains to GitHub.
Troubleshoot software delivery, deployment, source control, security, and infrastructure challenges across enterprise environments.
Lead the adoption of AI-enabled software development practices across the SDLC, leveraging GitHub Copilot and emerging AI engineering capabilities.
Advise clients on GitHub Copilot strategy, responsible AI governance, security, licensing, usage measurement, and cost management to improve adoption and business value.
Establish adoption and value-realization frameworks that connect GitHub Copilot usage, license utilization, AI consumption, delivery outcomes, quality, and developer experience to measurable client goals.
Guide clients in managing AI costs through fit-for-purpose model selection, efficient prompting and context patterns, usage guardrails, license optimization, and ongoing consumption reviews.
Design and implement AI-assisted workflows for coding, testing, code review, documentation, troubleshooting, and developer productivity improvement.
Develop reusable AI-enabled engineering accelerators, playbooks, and reference architectures that improve software quality, delivery speed, and engineering effectiveness.
Partner with business, engineering, and technology leaders to identify, prioritize, and scale AI-driven transformation opportunities across the SDLC.
Drive adoption of AI-enabled engineering practices utilizing GitHub Copilot and emerging software engineering capabilities.
Coach client leaders, engineers, architects, and developer champions on effective prompting, context management, human review, secure usage, and other GitHub Copilot best practices.
Continuously improve reliability, security, governance, compliance, and operational effectiveness across software delivery platforms.