Senior AI Full stack Software Engineer

Success Profile

What makes a successful Senior AI Full stack Software Engineer? Here are the top traits.

• Conceptual
• Proactive
• Problem-Solver
• Strategic
• Tech-Savvy
• Visual Thinker

Culture

Innovate
Foster a digital mindset to drive IT transformation across McKesson through our evolving data and technology tools.
Grow
Join a supportive environment where you can advance your career and develop both personally and professionally.

Benefits

• Coverage you can rely on- Medical, Dental, and Vision
• Health Spending Accounts
• Flexible Spending Accounts
• Benefits that go beyond your base pay- 401(k) (U.S.)
• Pension (Canada)
• Employee Stock Purchase Plan
• Mental Health Programs
• Flexible Schedules
• Paid Time Off
• Wellness Program
• Education Reimbursement
• Volunteer Opportunities
• Flexible Work Environment
• A culture powered by belonging

Responsibility

McKesson is an impact-driven, Fortune 10 company that touches virtually every aspect of healthcare. We are known for delivering insights, products, and services that make quality care more accessible and affordable. Here, we focus on the health, happiness, and well-being of you and those we serve – we care.

Key Responsibilities

• Lead AI-Driven Healthcare Solutions: Design and deploy AI applications that support decision-making, patient engagement, and operational efficiency.
• Integrate AI into EHRs and Clinical Systems: Build scalable systems that incorporate LLMs, voice/image recognition, and document parsing into existing healthcare IT infrastructure.
• Develop and Optimize Data Pipelines: Ensure secure, HIPAA-compliant data pipelines for training and deploying AI models using structured and unstructured healthcare data (e.g., clinical notes, imaging, lab results).
• Model Evaluation and Compliance: Apply rigorous evaluation metrics (e.g., sensitivity, specificity, AUC-ROC) and ensure models meet regulatory and ethical standards.
• Mentor and Lead: Guide junior engineers and contribute to the strategic direction of AI initiatives within the organization.
• Rapid AI prototyping and iteration with product representatives to vet multiple concepts

Minimum Qualifications

• 10+ years of software engineering experience, with 4+ years in AI/ML development.
• B.S. degree in Computer Science or related engineering discipline, or equivalent experience

Critical Skills

• 2+ years of experience building AI solutions in healthcare or life sciences.
• Deep understanding of healthcare data standards (e.g., HL7, FHIR) and compliance frameworks (e.g., HIPAA, GDPR).
• Healthcare AI Expertise: Proven ability to build AI models for clinical NLP, medical imaging, patient risk stratification, and care personalization.
• LLM & RAG Systems: Skilled in building retrieval-augmented generation systems using tools like Pydantic, Semantic Kernel, LangChain, LlamaIndex, and vector databases.
• Experienced in creating custom AI agents or spec-driven tools.
• Experience writing skills for Claude, Copilot, Codex etc.
• Prompt Engineering & Optimization: Advanced techniques for prompt tuning, caching, and benchmarking.
• Full Stack Development: Proficiency in Python, Node.js, and modern web frameworks.

Preferred Skills

• Cloud & DevOps: Experience with secure cloud environments (AWS/GCP/Azure), containerization (Docker, Kubernetes), and CI/CD pipelines.
• AI Tooling: Familiarity with OpenAI, Hugging Face, PyDanticAI, TensorFlow, PyTorch, and healthcare-specific AI libraries.
• Communication & Leadership: Ability to communicate complex AI concepts to clinical and executive stakeholders and lead cross-functional teams.
• Experience mentoring and developing juniors in development and AI concepts/best practices.