Build and enhance AI-enabled applications using LLMs, RAG patterns, agentic workflows, and multi-agent system design.
Architect and deliver cloud-native solutions using Microsoft Azure, Kubernetes, containers, microservices, and event-driven systems.
Lead technical design discussions and help define software architecture, engineering standards, and reusable development patterns.
Improve CI/CD pipelines, DevSecOps practices, test automation, monitoring, and platform automation.
Troubleshoot complex production and non-production issues; analyze root causes and recommend long-term solutions.
Partner with cross-functional teams to deliver secure, compliant, reliable, and maintainable software in a regulated enterprise environment.
Mentor engineers through code reviews, technical guidance, and shared best practices.
Basic Requirements
7+ years of professional software engineering experience, including enterprise-scale application development.
Experience building applications with Java, Python, React, JavaScript/TypeScript, REST APIs, or related full-stack technologies.
Experience designing, developing, and optimizing database solutions using MongoDB, PostgreSQL, relational data models, document databases, query optimization, indexing, and data integration patterns.
Hands-on experience with cloud-native architecture, preferably Azure, Kubernetes, containers, microservices, or serverless patterns.
Hands-on experience with AI-assisted software development or agentic coding tools and practices, including Claude Code, GitHub Copilot, code analysis, automated test generation, documentation support, and developer productivity workflows.
Experience designing or integrating APIs, distributed systems, event-driven services, or enterprise integrations.
Experience with CI/CD pipelines, DevOps or DevSecOps practices, Git-based workflows, automated testing, and release processes.
Experience applying secure coding, software quality, scalability, reliability, and maintainability practices.
Experience working in Agile delivery environments with product, architecture, security, and operations partners.
Bachelor’s degree in Computer Science, Engineering, Information Technology, or related field, or equivalent experience.
Preferred Skills/Experience
Experience building AI applications using LLMs, RAG, vector databases, prompt engineering, orchestration frameworks, or agentic AI patterns.
Experience with multi-agent systems, autonomous workflows, AI copilots, or AI-assisted automation.
Experience with Azure services, Kubernetes operations, event streaming, messaging platforms, or API gateways.
Experience with MongoDB, PostgreSQL, database performance tuning, schema design, indexing strategies, data migration, and secure data access patterns.
Experience contributing to open-source frameworks, internal developer platforms, reusable libraries, or engineering accelerators.
Experience with observability tools, infrastructure as code, policy-as-code, SRE practices, or platform engineering.
Experience applying AI-assisted software development and agentic coding capabilities across the SDLC, including code generation, code review, repository analysis, test automation, documentation, risk detection, and developer productivity improvement.
Experience working in healthcare, regulated technology, security-conscious, or compliance-driven environments.
Travel / Work Environment / Physical Requirements
Work model may be remote, hybrid, or office-based depending on business and team needs.
Occasional travel may be required for team collaboration, planning, or business meetings.
Ability to work at a computer for extended periods in a standard office or remote-work environment.
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
$99,100 - $132,100
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McKesson Talent Advisors will never solicit money or credit card information in connection with a McKesson job application.
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McKesson job postings are posted on our career site: careers.mckesson.com.
McKesson is an Equal Opportunity Employer
McKesson provides equal employment opportunities to applicants and employees, without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, disability, age, genetic information, or any other legally protected category. For additional information on McKesson’s full Equal Employment Opportunity policies, visit our Equal Employment Opportunity page.
McKesson is committed to being an Equal Employment Opportunity Employer and offers opportunities to all job seekers including job seekers with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, please contact us by sending an email to (United States) Disability_Accommodation@McKesson.com or (Canada) Accessibility@mckesson.ca. Resumes or CVs submitted to this email box will not be accepted.
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