Forward Deployed Engineer - FDE - Remote

UnitedHealth Group•San Diego, CA

15h•Remote

About The Position

The Forward Deployed Engineer (FDE) operates at the intersection of consulting, engineering, and client delivery—partnering directly with healthcare payers and providers to design, build, and scale AI-powered solutions that address complex business and operational challenges. This role is deeply embedded with clients, leading engagements from discovery through deployment. The FDE translates ambiguous business needs into production-grade systems, combining strong technical expertise with a consultative mindset. Success in this role requires the ability to influence stakeholders, shape solution strategy, and deliver high-impact outcomes in dynamic client environments. If you are located in San Diego, CA, you will have the flexibility to work remotely as you take on some tough challenges.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, or related field
8+ years of hands-on software engineering experience in deploying distributed systems and cloud-native solutions
7+ years of experience operating in a consulting or advisory capacity, including structuring ambiguous problems, developing solution recommendations, and delivering against client or business objectives
Experience working in client-facing engagements, including partnering directly with stakeholders to understand needs, communicate solutions, and support delivery in real-world environments
Experience building and deploying AI/ML solutions, including familiarity with LLMs, prompt engineering, and model deployment patterns
Experience structuring ambiguous problems and driving them to clear, actionable solutions
Experience working in cloud environments (e.g., Azure, AWS, GCP)
Proficiency in modern development frameworks, APIs, and data integration approaches
Advanced user capability on CodeX, Claude, etc. and other AI productivity tools
Proven ability to lead client engagements, including discovery, solution design, and delivery
Proven solid stakeholder management skills, with the ability to influence both technical and executive audiences
Proven excellent communication and storytelling skills, with the ability to adapt messaging to different audiences

Nice To Haves

Master’s degree in a technical discipline (AI/ML, Data Science, Software Engineering)
Healthcare Domain Expertise; understanding of healthcare payer and/or provider operations (e.g., claims, utilization management, care delivery, revenue cycle)
Familiarity with healthcare data, regulatory requirements, and interoperability considerations
Proven to be comfortable operating in fast-paced, ambiguous environments with evolving client needs
Proven solid collaboration mindset with the ability to work across distributed and cross-functional teams
Proven entrepreneurial, solution-oriented approach with a bias toward action and outcomes

Responsibilities

Partner directly with healthcare clients to understand strategic priorities, operational challenges, and digital transformation goals
Lead discovery sessions, workshops, and solution design engagements with both technical and business stakeholders
Act as a trusted advisor, guiding clients on how to apply AI/ML capabilities to real-world healthcare use cases (e.g., claims, revenue cycle, clinical workflows, member experience)
Translate client needs into clear problem statements, solution architectures, and delivery roadmaps
Design scalable, secure, and compliant AI-powered solutions aligned to healthcare industry requirements
Architect end-to-end systems integrating LLMs, machine learning models, APIs, and enterprise platforms
Evaluate trade-offs between approaches (e.g., build vs. orchestrate, model selection, latency vs. accuracy) and communicate recommendations clearly to stakeholders
Ensure solutions are designed for real-world deployment, maintainability, and integration with existing client ecosystems
Build and deploy production-grade AI applications, including LLM-based workflows, copilots, and intelligent automation solutions
Integrate AI agents and automation into client environments, optimizing for performance, scalability, and reliability
Rapidly prototype solutions to validate concepts, iterate with client feedback, and accelerate time-to-value
Troubleshoot complex technical challenges across distributed systems and cloud platforms
Bridge business, clinical, and technical perspectives—translating between stakeholders to ensure alignment and clarity
Collaborate with product, platform, and engineering teams to bring reusable capabilities into client deployments
Communicate complex technical concepts in a way that is accessible and actionable for non-technical stakeholders
Own delivery outcomes from initial discovery through production deployment and scale
Drive measurable impact for clients (e.g., operational efficiency, cost savings, improved experience)
Build strong, trusted relationships with client stakeholders to enable long-term partnerships
Contribute to reusable assets, playbooks, and best practices to accelerate future client engagements