Forward Deployed Engineering, US Oncology

McKesson; Mississauga; On-site; CAD 110,000 - 160,000; Full time

Job summary

McKesson, a Fortune 10 healthcare company, seeks a Lead Forward Deployed Engineer to partner with business and operational teams to turn complex problems into AI-enabled solutions. This hands-on role connects business needs with technology and moves ideas from discovery to prototypes, then production with multiple teams including AI Application Engineering and MLOps.

You will define production pathways, validate value with users, and ensure a scalable, governed solution, while mentoring

Qualifications

• 8+ years of relevant experience building, integrating, or delivering enterprise software solutions.
• Hands-on software engineering capability with APIs, data, integrations, and cloud-based patterns.
• Experience translating ambiguous business problems into working technical solutions, prototypes, or proofs of concept.
• Experience working directly with business executives and operational leaders.

Responsibilities

• Embed with practice and business teams to understand workflows, user needs, and outcomes.
• Lead discovery workshops, workflow assessments, and problem framing with executives and clinical teams.
• Translate business needs into clear problem statements, hypotheses, and prototype scopes.
• Advise where AI, automation, data, or workflow tech is appropriate and communicate risks and tradeoffs.
• Design pragmatic solution approaches using enterprise technologies and available data assets.
• Build prototypes and proofs of concept to test feasibility with representative users.
• Demonstrate prototypes, gather feedback, and decide to stop, refine, or advance.
• Collaborate with AI Application Engineers, Data Engineers, MLOps, security, and product leaders.
• Lead solution handoff to engineering teams and support production readiness.
• Capture patterns and lessons learned to improve speed and consistency.

Job description

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.

What you do at McKesson matters. We foster a culture where you can grow, make an impact, and are empowered to bring new ideas. Together, we thrive as we shape the future of health for patients, our communities, and our people. If you want to be part of tomorrow's health today, we want to hear from you.

Current Need

The US Oncology Network is seeking a Lead Forward Deployed Engineer (FDE) to partner directly with business and operational teams to turn complex, high-value problems into validated AI-enabled solutions. This is a hands‑on, business‑embedded engineering role for someone who can work comfortably in ambiguity, connect business needs with technology, and rapidly move ideas from discovery to working prototypes.

The FDE leads the front end of the AI delivery lifecycle. You will understand workflows, frame problems, assess technical options, build and test prototypes, and validate value with users. Once a concept is validated, you will define a clear production path and work with AI Application Engineering, Data Engineering, MLOps, architecture, security, compliance, and operational teams to transition the solution for industrialization and scale.

This role requires strong software engineering judgment, broad technical fluency, and exceptional stakeholder engagement. The FDE role provides technical coherence from problem through prototype, preserves the intended business outcome, and ensures downstream teams have the context needed to deliver a scalable, governed solution.

Key Responsibilities

• Embed with practice and business teams to understand workflows, user needs, operational constraints, pain points, and desired outcomes.
• Lead discovery workshops, workflow assessments, and problem‑framing sessions with executives, physicians, clinical teams, revenue cycle leaders, operational teams, and subject matter experts.
• Translate ambiguous business needs into clear problem statements, testable hypotheses, technical options, prototype scopes, and measurable success criteria.
• Advise stakeholders where AI, automation, data, or workflow technology is appropriate and clearly communicate capabilities, limitations, risks, and tradeoffs.
• Design pragmatic solution approaches using approved enterprise technologies, architecture patterns, and available data assets.
• Build working prototypes, proofs of concept, and thin-slice solutions that test feasibility and enable meaningful feedback from representative users.
• Apply sound software engineering practices so prototype code, interfaces, and design decisions can be understood, reused, or extended by delivery teams.
• Use AI‑enabled patterns such as retrieval‑augmented generation, copilots, agents, semantic search, decision support, and workflow automation when appropriate to the problem.
• Demonstrate prototypes, gather user and technical feedback, iterate rapidly, and recommend whether to stop, refine, or advance the work.
• Identify application, data, integration, security, architecture, operational, and governance dependencies early in the engagement.
• Collaborate with AI Application Engineers, Data Engineers, MLOps Engineers, architects, product leaders, security, compliance, and business SMEs to shape an executable delivery path.
• Define solution requirements, dependencies, and acceptance criteria for production delivery.
• Assess production readiness and document risks, decisions, and required controls.
• Lead solution handoff to engineering teams and support successful implementation.
• Drive reuse by capturing patterns, assets, and lessons learned across engagements.
• Contribute to FDE playbooks, prototype standards, reusable asset libraries, and delivery practices that improve speed and consistency.
• Mentor engineers in business discovery, problem framing, rapid prototyping, and technical stakeholder communication.

Minimum Requirement

Degree or equivalent experience and typically 8+ years of relevant experience in software engineering, solution engineering, solution architecture, technical consulting, enterprise application delivery, or digital transformation.

Education

Bachelor's degree in Computer Science, Engineering, Information Systems, or a related field, or equivalent practical experience.

Critical Skills

• 8+ years of relevant experience building, integrating, or delivering enterprise software solutions.
• Strong hands‑on software engineering capability, including the ability to work with APIs, data, integrations, and modern cloud‑based application patterns.
• Demonstrated experience translating ambiguous business problems into working technical solutions, prototypes, or proofs of concept.
• Experience working directly with business executives, operational leaders, sub