COMPANY: McKesson Corporation

POSITION: Senior Quality & DevOps Engineer

LOCATION: Richmond, VA (Remote Eligible)

JOB DUTIES:

This role represents the evolution of modern quality engineering from a testing-centric discipline to an engineering architecture and governance function. The successful candidate will establish the frameworks, controls, validation systems, and accountability mechanisms that enable engineering teams to deliver high-quality software with speed, predictability, and transparency.

Strategic Leadership

Lead the quality architecture, engineering effectiveness, and delivery governance strategy across multiple data and software products. Design and govern frameworks that embed quality directly into the software development lifecycle, integrating requirements, specifications, development, validation, testing, release management, traceability, and production operations into a unified delivery system. Establish organizational standards, quality controls, and accountability models that ensure software quality is engineered into the process rather than inspected after implementation.

Serve as the organizational authority for software delivery governance, defining how code moves from specification through production release. Establish validation gates, traceability requirements, release controls, audit mechanisms, and engineering standards that create predictable, transparent, and compliant software delivery processes suitable for highly regulated and enterprise environments.

Drive adoption of modern engineering practices including Spec-Driven Development, automated quality gates, AI-assisted development workflows, and continuous delivery. Establish engineering accountability frameworks that distribute ownership of quality across development teams. Mentor engineers and technical leaders in the adoption of standards, automation, specifications, validation practices, and delivery controls that enable consistent production-ready software delivery.

Production Environment & Platform Leadership: Guide or direct the operational lifecycle and architecture of production environments. Establish self-service deployment pipelines, infrastructure as code (IaC) governance, and production readiness standards that empower development teams while maintaining high availability and compliance.

Observability & Monitoring Strategy: Define and implement end-to-end monitoring, logging, and observability frameworks to ensure proactive incident detection, quick telemetry feedback loops, and rapid mean time to resolution (MTTR).

Continuous Delivery & Operations Integration: Bridge quality engineering and platform operations by standardizing deployment validation, progressive delivery mechanisms (canary/blue-green deployments), automated rollback strategies, and automated health checks across all environments.

Organizational Impact

Analyze development workflows and implement scalable solutions that improve engineering productivity, delivery confidence, and product reliability.

Technical Execution

Partner with software engineers, product managers, DevOps engineers, cloud engineers, and technical leadership to embed quality throughout the software development lifecycle. Architect and maintain automated testing strategies spanning API, UI, integration, performance, and end-to-end validation. Develop and enhance release management processes, deployment governance, and quality metrics to support enterprise-scale product delivery.

AI & Future-State Engineering

Lead the design and governance of AI-assisted engineering workflows, agentic development practices, and autonomous validation systems. Establish structured human-in-the-loop review models, agentic validation loops, prompt-driven development patterns, automated quality feedback mechanisms, token-efficient execution strategies, and specification-driven delivery frameworks that improve engineering productivity while maintaining quality, traceability, and compliance standards.

Lead the adoption and governance of AI-assisted software engineering practices, including agentic coding workflows, automated validation frameworks, specification-driven execution models, and engineering effectiveness metrics. Establish repeatable patterns for human-agent collaboration that improve software quality, reduce delivery risk, and maximize the efficiency of AI-generated outputs.

Technical Domains

Support cloud-native application development and full-stack solutions through quality engineering leadership, test architecture, data validation, and operational excellence practices.

Support and guide enterprise cloud deployment architectures, Infrastructure as Code (IaC), CI/CD automation pipelines, container orchestration, production environment lifecycle management, real-time monitoring, telemetry, APM, and more.

REQUIREMENTS:

Bachelor's Degree in Computer Science, Information Systems, Software Engineering, Computer Engineering, or a related field and Twelve (12) years of experience in software engineering, quality engineering, DevOps engineering, or a related technical field.

Applicant must have demonstrated experience in the following skills:

• Architecting and governing enterprise engineering frameworks that integrate specifications, development, validation, testing, release management, traceability, accountability, and operational controls into a unified software delivery lifecycle;
• Designing and developing automated testing solutions for full-stack applications using modern frameworks and technologies including React, JavaScript/TypeScript, Python, Flask APIs, Cypress, Playwright, Postman, and Web Services;
• Building and maintaining manual and automated validation strategies including unit, integration, API, regression, end-to-end, smoke, and performance testing across distributed systems;
• Establishing CI/CD pipelines and DevOps delivery practices using Git, GitHub, Azure DevOps, Jenkins, GitLab, or equivalent platforms to improve software quality and deployment consistency;
• Developing and implementing release management processes, quality gates, deployment governance controls, and engineering standards to support scalable software delivery;
• Working with cloud-native platforms and modern software architectures including microservices, containerized applications, cloud infrastructure, and distributed systems;
• Utilizing SQL, relational databases, data validation techniques, and data modeling concepts to verify application integrity, business rules, and data quality across complex systems;
• Applying Agile methodologies, test-driven development, specification-driven development, and continuous improvement practices to increase engineering effectiveness and delivery predictability;
• Leveraging AI-assisted and agentic coding platforms to accelerate software delivery, automate quality workflows, improve developer productivity, and enhance engineering outcomes;
• Monitoring software quality, operational performance, and delivery metrics through observability, reporting, analytics, and engineering effectiveness measurements;
• Proven track record leading DevOps initiatives, managing cloud-native production environments, configuring automated deployment pipelines, and establishing observability standards (metrics, logs, traces) in high-scale enterprise ecosystems;
• Leading cross-functional technical initiatives, mentoring engineers, influencing engineering standards, and driving organization-wide adoption of quality engineering best practices;
• Collaborating with software engineering, product, architecture, security, and operations teams to deliver highly reliable, scalable, and compliant technology solutions;
• Lead the adoption and governance of AI-assisted software engineering practices, including agentic coding workflows, automated validation frameworks, specification-driven execution models, and engineering effectiveness metrics. Establish repeatable patterns for human-agent collaboration that improve software quality, reduce delivery risk, and maximize the efficiency of AI-generated outputs;
• Designing and governing engineering effectiveness systems that leverage agentic development practices, structured validation loops, AI-assisted software delivery, context management, token-efficiency optimization, automated quality gates, specification-driven execution models, and human-in-the-loop and manual checkpoints to improve productivity, predictability, and software quality.

PREFERRED QUALIFICATIONS:

• Experience leading quality strategy for enterprise software platforms and data products.
• Experience establishing organization-wide engineering effectiveness programs.
• Strong understanding of software architecture, system design, and cloud engineering principles.
• Experience creating and sustaining automated testing frameworks and manual testing practices at scale.
• Experience supporting regulated industries including healthcare, life sciences, financial services, or other compliance-driven environments.
• Demonstrated ability to influence technical direction without direct management authority.
• Strong written and verbal communication skills with executive-level stakeholders.
• Proven track record of delivering high-quality software products with minimal production defects.
• AWS, Azure, GCP, or OCI Certified Cloud Architect demonstrating foundational expertise in designing, deploying, and maintaining secure, scalable cloud environments.

CRITICAL SUCCESS FACTORS:

• Acts as a force multiplier across engineering teams by improving how software is designed, developed, tested, and released.
• Develops and operationalizes agentic engineering practices that enable developers and AI systems to work together effectively through structured specifications, validation loops, automated quality controls, and token-efficient execution patterns.
• Drives quality ownership throughout the engineering organization rather than functioning as a traditional testing or DevOps resource.
• Establishes scalable frameworks and governance that reduce operational and delivery risk.
• Balances strategic leadership with hands-on technical contribution.
• Enables predictable, audit-ready, and high-confidence software delivery in support of organizational growth objectives.
• Establishes organizational frameworks that make quality an engineered outcome of the software delivery process, reducing reliance on downstream inspection and increasing developer ownership, accountability, and delivery confidence.
• Creates scalable governance systems that provide traceability from business requirements and technical specifications through development, validation, deployment, and production operations.

We are proud to offer a competitive compensation package at McKesson as part of our Total Rewards. This is determined by several factors, including performance, experience and skills, equity, regular job market evaluations, and geographical markets. The pay range shown below is aligned with McKesson's pay philosophy, and pay will always be compliant with any applicable regulations. In addition to base pay, other compensation, such as an annual bonus or long-term incentive opportunities may be offered. For more information regarding benefits at McKesson, please click here.

Our Base Pay Range for this position

$120,000 - $200,000

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