Forward Deployed Engineering, US Oncology

Description

The company is a large healthcare organisation whose work covers most parts of the health system, including insights, products and services aimed at making quality care easier to reach and more affordable.

The US Oncology Network is hiring a Lead Forward Deployed Engineer (FDE) to work directly with business and operations teams. The job turns hard, high-value problems into AI-enabled solutions that have been tested against real needs.

This is a hands-on engineering role embedded in the business. It suits someone who is comfortable with unclear problems, can link business needs to technology, and can move an idea quickly from discovery to a working prototype.

The FDE owns the early part of the AI delivery lifecycle: learning workflows, framing problems, comparing technical options, building and testing prototypes, and checking value with users. Once a concept is proven, the FDE sets a clear route to production and works with application, data, MLOps, architecture, security, compliance and operations teams to move the solution toward scale.

The role calls for solid software engineering judgment, wide technical knowledge and strong stakeholder skills. The FDE keeps the technical thread from problem to prototype, protects the intended business result, and gives downstream teams the context they need to deliver a scalable, governed solution.

Responsibilities

• Work alongside practice and business teams to learn their workflows, user needs, operational limits, pain points and goals.
• Run discovery workshops, workflow reviews and problem-framing sessions with executives, physicians, clinical staff, revenue cycle leaders, operations teams and subject matter experts.
• Turn vague business needs into clear problem statements, testable hypotheses, technical options, prototype scopes and measurable success criteria.
• Advise stakeholders on where AI, automation, data or workflow tools fit, and explain their capabilities, limits, risks and trade-offs clearly.
• Design practical solutions using approved enterprise technology, architecture patterns and the data available.
• Build working prototypes, proofs of concept and thin-slice solutions that test feasibility and collect useful feedback from representative users.
• Apply solid software engineering practice so that prototype code, interfaces and design decisions can be understood, reused or extended by delivery teams.
• Use AI patterns such as retrieval-augmented generation, copilots, agents, semantic search, decision support and workflow automation where they suit the problem.
• Demonstrate prototypes, gather user and technical feedback, iterate quickly, and recommend whether to stop, refine or move the work forward.
• Spot application, data, integration, security, architecture, operational and governance dependencies early in the engagement.
• Work with AI application, data and MLOps engineers, architects, product leaders, security, compliance and business experts to shape a workable delivery path.
• Define solution requirements, dependencies and acceptance criteria for production delivery.
• Assess production readiness and document risks, decisions and the controls required.
• Lead the handoff of solutions to engineering teams and support their implementation.
• Capture patterns, assets and lessons learned from each engagement so they can be reused.
• Contribute to FDE playbooks, prototype standards, reusable asset libraries and delivery practices that improve speed and consistency.
• Coach engineers in business discovery, problem framing, rapid prototyping and communicating with technical stakeholders.

Requirements

• A degree or equivalent experience, typically with 8+ years in software engineering, solution engineering, solution architecture, technical consulting, enterprise application delivery or digital transformation.
• A bachelor's degree in computer science, engineering, information systems or a related field, or equivalent practical experience.
• 8+ years building, integrating, troubleshooting or delivering enterprise software.
• Strong hands-on full-stack experience and troubleshooting across modern web apps, APIs, data, AI services, identity, security and cloud infrastructure.
• Hands-on work with React, Node.js, TypeScript, Python and modern web application architecture.
• Skill in API diagnostics and browser troubleshooting, covering network requests, authentication, application state, errors and performance.
• Hands-on experience with Snowflake and Databricks, including data pipelines, lineage, reconciliation, data quality and performance tuning.
• Experience using logs, metrics, traces, dashboards and alerts to find root causes and confirm end-to-end behaviour.
• Proven ability to diagnose problems across application, integration, data, AI, security and infrastructure layers and choose the right fix.
• Proven record of turning vague 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 speed up development while reviewing, testing, securing and refining the output to meet the company 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 compare technical options, explain trade-offs and recommend a fit-for-purpose approach even when requirements are incomplete.
• Excellent written, verbal, facilitation and presentation skills, with the ability to explain complex technical ideas to technical and non-technical audiences.
• Ability to work independently on complex or highly visible initiatives while keeping stakeholders aligned on outcomes, scope, risks and ownership.
• Nice to have: healthcare experience in oncology, clinical operations, revenue cycle, patient access, care management, provider operations or a related area.
• Nice to have: experience with Azure AI services, Databricks, Python, C, TypeScript, REST APIs, ServiceNow, Salesforce, Power BI or comparable enterprise technology.
• Nice to have: experience with retrieval-augmented generation, prompt and response evaluation, agentic workflows, semantic search or AI guardrails.
• Nice to have: experience in regulated environments applying Responsible AI, cybersecurity, privacy, compliance and data governance requirements.
• Nice to have: experience with Agile, product-led, innovation lab, consulting or pod-based delivery models.
• Nice to have: ability to learn unfamiliar business domains and technology environments quickly.
• Nice to have: strong empathy for customers and the business, a focus on outcomes, sound engineering judgment, and the ability to influence without direct authority.

Conditions

Flex and Connect work model, with office attendance required two (2) days per week.

Pay is set by factors such as performance, experience and skills, equity, periodic market reviews and location. Base pay is $122,100 to $162,800. An annual bonus or long-term incentive may also be offered on top of base pay.

The company is an equal opportunity employer.

Recruiters will never ask for money or card details. Official roles are listed only at the company's site.

Benefits

• Access to the company's Total Rewards package.