Forward Deployed Engineer - FDE - Remote

UnitedHealth Group•Chicago, IL

16h•Remote

About The Position

The Forward Deployed Engineer (FDE) is a hands-on engineering role focused on building and deploying AI-powered solutions within client environments. Working as part of client-facing delivery teams, this role partners with senior engineers and consulting leads to implement scalable, production-ready systems for healthcare payers and providers. FDEs contribute directly to solution delivery—translating defined requirements into working systems, building integrations, and supporting deployments. While primarily focused on engineering execution, the role also operates in client settings, requiring strong collaboration and the ability to support technical discussions with both engineering and business stakeholders. If you are located in Chicago, IL, 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
3+ years of proficient experience in at least one programming language (e.g., Python, Java, SQL)
2+ years of experience operating in a consulting or advisory capacity, including structuring ambiguous problems, developing solution recommendations, and delivering against client or business objectives
Demonstrated experience working in client-facing engagements, including partnering directly with stakeholders to understand needs, communicate solutions, and support delivery in real-world environments
Experience working with APIs, data pipelines, or distributed systems
Familiarity with cloud platforms (e.g., AWS, Azure, or GCP)
Exposure to AI/ML concepts, including LLMs and prompt engineering
Demonstrate advanced user capability on CodeX, Claude, etc. and other AI productivity tools
Demonstrated ability to work effectively in client-facing delivery environments
Demonstrated solid collaboration skills and ability to operate within structured project teams
Demonstrated clear communication skills for working with both technical and non-technical stakeholders
Demonstrated ability to execute against defined requirements and evolving priorities

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 considerations (e.g., privacy, compliance)
Demonstrated solid execution focus with attention to detail and code quality
Demonstrated ability to work in fast-paced environments with multiple priorities
Willingness to take ownership of assigned components and deliver reliably
Continuous learning mindset, particularly in AI and emerging technologies

Responsibilities

Build and deploy AI-powered solutions, including LLM-based workflows, copilots, and automation tools in client environments
Implement integrations between AI models, APIs, and enterprise healthcare systems
Translate defined solution designs into high-quality, production-ready code
Contribute to end-to-end delivery by supporting development, testing, and deployment activities
Develop solution components using modern programming languages (e.g., Python, Java, SQL) and engineering frameworks
Work with distributed systems and cloud platforms to support scalable, reliable deployments
Assist with data preparation, prompt configuration, and model integration for AI-driven solutions
Troubleshoot and resolve technical issues during development and deployment
Work alongside senior engineers and consulting leads in client engagements across healthcare payer and provider organizations
Support technical discussions and working sessions with client stakeholders
Help execute on defined project plans, timelines, and deliverables
Contribute to iterative development cycles, incorporating client and team feedback
Partner with cross-functional teams, including engineering, platform, and product teams, to deliver integrated solutions
Translate technical requirements into actionable development tasks
Communicate progress, risks, and technical considerations clearly within the team
Support alignment between technical implementation and client expectations
Document solution components, integration points, and deployment processes
Support knowledge transfer to client technical teams to enable adoption and sustainability
Contribute to reusable implementation patterns, assets, and playbooks