Lead Solutions Engineer - Remote

Our people are the foundation of our success. By joining our growing team at Sarah Cannon Research Institute (SCRI), a subsidiary of McKesson, you will have the opportunity to become part of one of the largest community-based cancer programs to advance oncology treatments and improve outcomes for cancer patients across the globe. We look for mission-driven candidates who have a desire to advance the fight against cancer and make a difference in the lives of patients diagnosed with cancer every day.

People who live with cancer - those who work to prevent it, fight it, and survive it - are at the heart of every decision we make. Bringing the most innovative medical minds together with the most passionate caregivers in their communities, we are transforming care and personalizing treatment. Through clinical excellence and cutting-edge research, SCRI is redefining cancer care around the world.

This position requires deep technical expertise, strong architectural judgment, and the ability to independently drive complex, ambiguous initiatives to completion. The role is not oversight only; it is focused on custom AI development, intelligent automation, and solution execution using large language models, agents, orchestration frameworks, and enterprise integrations.

In addition, this role is expected to evangelize and engage the business, translating opportunities and problems into tangible, trusted, production ready AI solutions that measurably improve productivity, quality, cycle time, and decision making across SCRI.

This is a remote position based in the United States. Relocation assistance and visa sponsorship are not available

• Independently design, build, and maintain:
• AI prompts and prompt libraries
• LLM based agents and copilots
• Chatbots, automation scripts, and end to end intelligent workflows
• Lead rapid prototyping and experimentation; convert successful pilots into scalable, production grade solutions
• Own the day-to-day technical health of deployed solutions, including monitoring, troubleshooting, performance tuning, and reliability improvements
• Build and maintain robust integrations with enterprise platforms using APIs, services, data pipelines, and workflow orchestration tools

• Serve as the end-to-end AI solution architect for assigned initiatives, making architectural decisions and implementing them hands on
• Define and standardize solution patterns for:
• Agent architectures (RAG, tool calling, multi agent orchestration)
• Integration and data flow design
• Environmental promotion and deployment strategies (dev/test/prod)
• Own delivery planning with clearly defined value metrics, success criteria, and timelines
• Proactively identify technical risks, trade offs, and dependencies and drive resolution

• Lead execution for high impact, enterprise level AI and automation use cases, particularly complex or manual processes with measurable value potential
• Translate loosely defined business problems into durable, production ready AI solutions
• Typical use cases include, but are not limited to:
• LLMbased agents for case intake, triage, summarization, and decision support
• Intelligent document processing across emails, PDFs, forms, and unstructured content
• Workflow automation for finance, operations, compliance, research, or shared services
• Embedded AI assistants integrated into enterprise systems to reduce manual effort, errors, and cycle time
• Partner closely with business owners to validate outputs, refine logic, and ensure solutions are adopted, trusted, and operationalized

• Ensure all solutions comply with enterprise AI governance standards, ethical AI principles, and corporate policies
• Design and implement securebydefault solutions, including documentation, traceability, monitoring, and audit readiness
• Anticipate and mitigate risks related to data privacy, access control, model behavior, hallucinations, bias, and operational resilience
• Partner with architecture, security, and data governance teams to ensure compliant solution design, especially within regulated environments

• Evangelize AI and intelligent automation capabilities across the organization by:
• Engaging business…