The QAE/DevOps Solutions Architect leads the design and implementation of enterprise-scale quality engineering, automation, and DevOps capabilities. This role will define end-to-end SDLC and QA architecture with a strong emphasis on Azure DevOps pipelines, CI/CD integration, governance, quality gates, and AI-assisted quality engineering practices. The QAE/DevOps Solutions Architect leads the evolution from manual testing to a Quality Assurance Engineering (QAE) function using data to drive to enterprise outcomes.

SKILLS

Duties and Responsibilities:

• Define QAE and DevOps automation architecture. Define and evolve the test technology stack, document the reference architecture, code standards, and repo structure the team builds against.
• Stay up to date on emerging technology in the Quality and DevOps space. Assess how new technologies can be leveraged to enhance quality services. Stay up to date on the quality implications for emerging technology in development, data, and analytical domains.
• Help lead and assist with the modernization of the end-to-end SDLC process and ensure our process and supporting technology stack aligns with emerging best practices.
• Design, implement, and optimize Azure DevOps CI/CD pipelines with integrated quality gates and governance controls. Establish enterprise standards for build, release, and deployment pipelines, including compliance and auditability.
• Integrate automated testing frameworks into CI/CD pipelines (UI, API, performance, data validation). Define and enforce QA governance models, including standards, controls, and best practices across teams.
• Participate in the automation backlog, consuming risk-ranked regression suites with a deliberate record of which test cases are automated and why. Identify and retire technical debt in the QA technology stack.
• Lead adoption of AI-assisted QA tools (e.g., test generation, defect prediction, intelligent automation).
• Partner with DevOps, engineering, and platform teams to ensure seamless end-to-end SDLC integration. Lead shift-left quality initiatives to embed testing early in the development lifecycle and shift-right processes to ensure learnings with Production incidents.
• Evaluate and select tools and frameworks for QA automation, pipeline optimization, and AI integration.
• Mentor QA and DevOps engineers on best practices for automation, pipelines, and governance.
• Drive continuous improvement of deployment reliability, speed, and quality metrics.
• Extend QA oversight onto AI agents and bot interactions, define rules/grades for bots and ensure parity of quality controls across human and virtual agents.

Knowledge, Skills, and Abilities:

• 10+ years of experience in QA, quality engineering, or test automation, including previous experience in an architect role.
• Previous experience leading QA manual-to-automation transformation
• Deep expertise in Azure DevOps (Platform Administration, Pipelines, Repos, Test Plans, Artifacts) with a strong focus on deployment pipelines.
• Proven experience designing and governing enterprise CI/CD pipelines.
• Strong experience with automation frameworks (Playwright, Selenium, or similar).
• Experience with API testing, data validation, and pipeline-integrated testing strategies.
• Strong scripting/programming skills (C#, Python, PowerShell, JMeter, or similar).
• Experience integrating QA into CI/CD workflows with enforceable quality gates, including regression, integration, performance, and other quality checks.
• Experience establishing governance frameworks for QA and DevOps practices.
• Strong understanding of modern SDLC, DevOps, and Agile practices.
• Data and analytics literacy to design QAE processes and interpret trends.

Preferred Qualifications

• Experience with infrastructure-as-code (Bicep, Terraform, ARM).
• Experience with containerization (Docker, Kubernetes).
• Experience with cloud-native architectures (Azure preferred).
• Experience with AI-assisted development or testing tools (e.g., GitHub Copilot, Claude Code, Cursor AI, AI test generation platforms).
• Experience with data platforms (Snowflake, dbt) is a plus.
• Familiarity with security, compliance, and enterprise AI governance policies.

Work-at-home requirements

• Must have the ability to provide a non-cellular High Speed Internet Service such as Fiber, DSL, or cable Modems for a home office.
• A minimum standard speed for optimal performance of 30x5 (30mpbs download x 5mpbs upload) is required.
• Latency (ping) response time lower than 80 ms
• Hotspots, satellite and wireless internet service is NOT allowed for this role.
• A dedicated space lacking ongoing interruptions to protect member PHI / HIPAA information

How we value you

• Competitive pay/salary ranges
• Incentive plan
• Health/Vision/Dental benefits effective day one
• 401(k) retirement plan: company match - dollar for dollar up to 4% employee contribution (pretax or Roth options) plus a 6% annual company contribution
• Robust employee well-being program
• Paid Time Off
• Personal Community Enrichment Time
• Company-provided Basic Life and AD&D
• Company-provided Short-Term & Long-Term Disability
• Tuition Assistance Program

While this is a remote opportunity, at this time G.E.H.A does not hire employees from U.S. territories or the following states: Alaska, Hawaii, California, Washington, Oregon, Colorado, Wyoming, Montana, New York, Connecticut, Vermont, Pennsylvania, Maine.

Please note that the salary information is a general guideline only. G.E.H.A considers factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience, education/training, key skills, internal peer equity, as well as, market and business considerations when extending an offer.

The target hiring range for this position is $123,398 - $156,106 USD. At G.E.H.A, the current maximum salary for this role is $173,946 USD. While initial compensation may vary based on experience and qualifications, there is a path to work toward this top rate through performance and continued growth within the organization.

G.E.H.A is headquartered in Lee's Summit, Missouri, in the Kansas City area. We recognize the importance of balance and flexibility and offer hybrid and work-from-home options for many of our roles.