Architect and implement AI-enabled backend services within a secure, cloud-native microservices environment.
Design and scale Intelligent Document Processing (IDP) pipelines to extract and validate data from claims, authorizations, and medical documentation.
Integrate LLMs and intelligent agents into clinical and claims workflows to streamline patient and provider interactions.
Build AI Agents that surface actionable insights from EHR, claims, and unstructured clinical data.
Translate ML outputs into decision-ready intelligence for providers, payers, and operations leaders.
Lead cross-functional architecture sessions, code reviews, and design workshops.
Mentor engineers in modern AI/ML development practices, scalable system design, and secure operations.
Partner with clinicians, operations staff, and compliance leaders to ensure solutions align with healthcare standards and patient impact goals.
Drive continuous improvement by identifying opportunities to enhance system performance, scalability, and maintainability.
Design scalable APIs and data models that support secure, interoperable data exchange across care coordination and claims systems.
Define architectural patterns and reusable components that accelerate development while ensuring compliance and performance.
Translate business and clinical requirements into technical designs that are intuitive for end-users and sustainable for engineering teams.
Create design documentation and technical blueprints that guide implementation and ensure alignment with enterprise healthcare standards.
Requirements
Bachelor’s Degree in Computer Science, Software Engineering, or a related technical field.
Experience in using and designing with Agent-2-Agent (A2A) and Model Context Protocols (MCP).
Strong communication skills with the ability to lead the team and drive product vision and mission to completion.
2+ years of software engineering experience, including at least 1 year in a leadership role guiding teams or projects.
Strong coding ability in Python, TypeScript, and Node.js.
Solid understanding of cloud-native microservices and event-driven architectures.
Strong understanding and experience in using AWS cloud native services and tools.
Hands-on experience applying LLMs, NLP, or Intelligent Document Processing (IDP) in production environments, using platforms such as OpenAI, Bedrock, Cohere, or Claude.
Knowledge of healthcare interoperability standards (FHIR, HL7, X12) and data governance in regulated environments.
Prior experience with claims adjudication, care coordination, or patient engagement systems is highly desirable.
Familiarity with AI-driven developer tools such as GitHub Copilot and Cursor.
Proven ability to collaborate effectively with both technical teams and healthcare stakeholders to deliver impactful solutions.
Unable to offer sponsorship at this time.
Benefits
Medical/Dental/Vision.
401k with Employer Match.
PTO + Federal Holidays.
Corporate Laptop.
Training Opportunities.
Remote Opportunity.
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