Healthcare AI Solution Engineer / Mid-FDE | REMOTE ROLE | (W2 Only)

Xlysi

$110K — $130K *
US-AnywhereRemote in Chicago, IL
Healthcare
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience in healthcare information technology, particularly in payer/provider domains.
  • Strong full-stack engineering skills with .NET, Python, and modern frameworks.
  • Proficient in cloud-native application development and Azure Cloud Architecture.
  • Expertise in microservices, API design, and modern database solutions.
  • Familiarity with healthcare interoperability standards like HL7/FHIR and EDI transactions.

Responsibilities

  • Partner with healthcare stakeholders to understand business workflows and challenges.
  • Translate complex healthcare needs into scalable technology solutions.
  • Design and develop end-to-end applications and enterprise architecture.
  • Create production-grade software using best engineering practices.
  • Drive automation and operational excellence through CI/CD and Infrastructure as Code.
  • Leverage AI technologies to enhance operations and improve business outcomes.
  • Mentor engineering teams and uphold standards of coding excellence.

Benefits

  • Opportunity to work at the intersection of healthcare and cutting-edge AI technology.
  • Engagement directly with business stakeholders to influence strategic outcomes.
  • Ownership of the complete solution lifecycle, from discovery to support.
  • Mentorship role that promotes engineering excellence within the team.
  • Chance to recommend and implement innovative solutions in healthcare.
Full Job Description
We are seeking a highly motivated and hands-on Healthcare AI Solution Engineer / Mid-FDE with the mindset of a Forward Deployed Engineer (FDE).

This role is designed for a rare engineering leader who can bridge business and technology-understanding complex healthcare operations, engaging directly with stakeholders, architecting scalable solutions, writing production-quality software, leveraging AI capabilities, and delivering measurable business outcomes.

The ideal candidate combines deep healthcare payer domain expertise with strong full-stack engineering, cloud, DevOps, AI, and architecture skills. This individual takes complete ownership from problem discovery through solution design, development, deployment, and continuous improvement.

Key Responsibilities
Partner directly with healthcare business stakeholders to understand workflows, challenges, and strategic objectives across payer operations.
Translate business needs into scalable, secure, cloud-native technology solutions.
Design enterprise solution architecture and build end-to-end applications across frontend, backend, APIs, integrations, data platforms, and AI capabilities.
Develop production-grade software using .NET, Python, modern frameworks, microservices, APIs, and engineering best practices.
Drive cloud engineering, DevOps, CI/CD, Infrastructure as Code, automation, monitoring, and operational excellence.
Leverage AI/LLMs, intelligent agents, and automation to improve healthcare operations, engineering productivity, and business outcomes.
Identify modernization opportunities and proactively recommend innovative solutions.
Own the complete solution lifecycle-from discovery, architecture, design, development, testing, deployment, and production support.
Mentor engineering teams and establish engineering excellence through architecture standards, coding practices, and innovation.

Required Healthcare Domain Experience
Strong expertise in one or more healthcare payer/provider domains, including:
Member Enrollment & Eligibility
Claims Processing & Adjudication
Provider Management
Healthcare EDI (HIPAA X12 Transactions)
Benefits Administration
Prior Authorization
Care Management (CM)
Utilization Management (UM)
Disease Management (DM)
Clinical Operations
Grievance & Appeals (G&A)
Payment Integrity

Experience with healthcare interoperability standards such as HL7/FHIR, APIs, and healthcare data exchange patterns is preferred.

Technical Skills
Full Stack Engineering
Full-stack application development
.NET / C#
Python
REST APIs & Microservices
Modern frontend frameworks
SQL / NoSQL databases
Event-driven architecture
Cloud & DevOps
Azure Cloud Architecture
Cloud-native application development
Azure DevOps / GitHub Actions
CI/CD automation
Containers & Kubernetes
Infrastructure as Code
Security, performance, and scalability engineering
AI & Intelligent Engineering
AI/LLM solution design and implementation
Generative AI applications
Agentic AI workflows
Retrieval Augmented Generation (RAG)
Intelligent automation
AI-enabled software engineering practices

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