Forward Deployed Engineering, US Oncology

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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.

• 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.

• 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.

• Bachelors degree in Computer Science Engineering Information Systems or a related field or equivalent practical experience.

• 8 years of experience building integrating troubleshooting or delivering enterprise software solutions.
• Strong hands-on full-stack engineering and troubleshooting experience across modern web applications APIs data AI services identity security and cloud infrastructure.
• Hands-on experience with React TypeScript Python and modern web application architecture.
• Proficiencyin API diagnostics and browser-based troubleshooting including network requests authentication application state errors and performance issues.
• Hands-on experience with Snowflake and Databricks including data pipelines lineage reconciliation data quality and performance tuning.
• Experience using logs metrics traces dashboards and alerting to perform root-cause analysis andvalidateend-to-end solution behavior.
• Demonstratedability to diagnose issues across applications integration data AI security and infrastructure layers anddeterminetheappropriate pathto resolution.
• Demonstratedexperience translating ambiguous business problems into working technical solutions prototypes or proofs of concept.
• Experience designing or prototyping AI-enabled solutions such as copilots agents retrieval-augmented generation semantic search decision support or workflow automation.
• Experience using AI coding assistants such as Claude or comparable tools to accelerate development while reviewing testing securing and refining generated code to meet McKesson engineering and quality standards.
• Sound understanding of software delivery enterprise integration security privacy Responsible AI data governance operational readiness and supportability.
• Experience working directly with business leaders subject matter experts end users and cross-functional engineering teams.
• Ability to evaluate technical alternatives explain tradeoffs and recommend fit-for-purpose approaches without complete requirements.
• Excellent written verbal facilitation and presentation skills with the ability to communicate complex technical concepts to technical and nontechnical audiences.
• Ability tooperateindependently across complex or highly visible initiatives while keeping stakeholders alignedonoutcomes scope risks and ownership.

• Healthcare industry experience supporting oncology clinical operations revenue cycle patient access care management provider operations or related domains.
• Experience with Azure AI services Databricks Python C# TypeScript REST APIs ServiceNow Salesforce Power BI or comparable enterprise technologies.
• Experience applying retrieval-augmented generation prompt and response evaluation agentic workflows semantic search or AI guardrails.
• Experience working in regulated environments and applying Responsible AI cybersecurity privacy compliance and data governance requirements.
• Experience with Agile product-led innovation lab consulting or pod-based delivery models.
• Ability to learn unfamiliar business domains and technology environments quickly.
• Strong customer and business empathy outcome orientation engineering judgment and ability to influence without direct authority.
  

Working Conditions

Flex & Connect work model with a requirement to be in the office two (2) days per week.

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 McKessons 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 pleaseclick here.

Our Base Pay Range for this position

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