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McKesson

Lead Intelligent Solutions Engineer

McKesson

. Design, build, and maintain AI prompts, prompt libraries, LLM-based agents, copilots, chatbots, automation scripts, and end-to-end intelligent workflows .

Posted 10/3/2026full-timeRemote • Texas • United StatesSeniorWebsite

Core Competencies

Role fit
Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and implementing AI solutions, including prompt engineering and enterprise integrations, while ensuring compliance with governance standards. Proven ability to lead complex projects, mentor teams, and translate business needs into scalable AI applications.

Highest-signal resume keywords
Machine Learning ExpertisePrompt EngineeringAI Solution ArchitectureEnterprise IntegrationRegulated Environment Experience

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills
Machine LearningPrompt EngineeringPythonJavaScriptAPI DevelopmentData TransformationRAG ArchitecturesOrchestration FrameworksDeployment PracticesGenerative AI
Soft Skills
Stakeholder InfluenceMentoringCollaborationProblem SolvingAdaptability
Tools & Technologies
Microsoft AI EcosystemCopilot StudioPower PlatformAzure AIAzure OpenAI
Certifications & Qualifications
Bachelor's DegreeMaster's Degree (Preferred)
Industry Keywords
HealthcareLife SciencesClinical ResearchComplianceData Privacy

Tech Stack

Tools & technologies
AzureJavaScriptPython

About the role

Key responsibilities & impact
  • Design, build, and maintain AI prompts, prompt libraries, LLM-based agents, copilots, chatbots, automation scripts, and end-to-end intelligent workflows
  • Lead rapid prototyping and experimentation and convert successful pilots into scalable, production-grade solutions
  • Own monitoring, troubleshooting, performance tuning, and reliability improvements for deployed solutions
  • Build and maintain enterprise integrations using APIs, services, data pipelines, and workflow orchestration tools
  • Serve as end-to-end AI solution architect and make hands-on architectural decisions
  • Define and standardize agent architectures, integration and data-flow designs, and dev/test/prod deployment strategies
  • Own delivery planning, value metrics, success criteria, and timelines
  • Identify technical risks, trade-offs, and dependencies and drive resolution
  • Lead high-impact enterprise AI and automation use cases
  • Translate loosely defined business problems into durable, production-ready AI solutions
  • Develop solutions for case intake, triage, summarization, decision support, intelligent document processing, workflow automation, and embedded AI assistants
  • Partner with business owners to validate outputs, refine logic, and operationalize trusted solutions
  • Ensure compliance with enterprise AI governance standards, ethical AI principles, and corporate policies
  • Design secure-by-default solutions with documentation, traceability, monitoring, and audit readiness
  • Mitigate risks related to data privacy, access control, model behavior, hallucinations, bias, and operational resilience
  • Partner with architecture, security, and data governance teams in regulated environments
  • Engage stakeholders and translate opportunities into concrete AI solution concepts
  • Produce technical documentation, user guides, and SOPs
  • Lead enablement sessions, workshops, and knowledge transfer
  • Mentor technical teams and influence AI and automation standards, patterns, and best practices
  • Collaborate with business and technology partners to improve AI-enhanced workflows

Requirements

What you’ll need
  • Bachelor's Degree required
  • Master's Degree preferred
  • At least 7 years of experience in machine learning
  • Healthcare, life sciences, or clinical research domain experience preferred
  • Experience delivering solutions in regulated, compliance-driven environments preferred
  • Proven experience delivering complex, production-grade AI and automation solutions as a hands-on builder
  • Deep proficiency in prompt engineering and applying Generative AI to enterprise workflows
  • Strong programming skills, typically Python and/or JavaScript
  • Experience with APIs, data transformation, version control, and deployment practices
  • Experience building agentic AI solutions, including RAG architectures, orchestration frameworks, and tool-calling patterns
  • Experience with Microsoft AI ecosystem tools such as Copilot Studio, Power Platform, Azure AI, or Azure OpenAI strongly preferred
  • Ability to maintain enterprise-grade security, reliability, and governance while rapidly prototyping
  • Ability to operate as a senior, end-to-end AI solution architect while remaining hands-on
  • Comfortable owning ambiguous, high-visibility initiatives with minimal direction
  • Strong stakeholder influence skills in a matrixed environment
  • Track record of translating concepts into shipped, adopted, enterprise solutions
  • Ability to operate at strategic, architectural, and engineering levels
  • Ability to influence change and drive adoption across teams
  • Ability to prioritize, execute, and deliver outcomes under evolving requirements
  • Must be based in the United States; visa sponsorship is not available

Benefits

Comp & perks
  • Comprehensive Total Rewards benefits supporting physical, mental, and financial well-being
  • Competitive compensation package
  • Annual bonus or long-term incentive opportunities may be offered
  • Equity may be included in compensation
  • Relocation assistance is not available
  • Visa sponsorship is not available