Full-Stack AI Engineer, AI Service Engines – Integration

This is a fully remote position, open to applicants in United States.

📋 Description

• Design and develop the adapter layer connecting AI service engines with the enterprise service bus.

• Create and manage FHIR PAS payloads.

• Construct a synchronous service engine for real-time AI tasks, such as letter generation.

• Modify the architecture of the current asynchronous Triage engine.

• Develop, deploy, and manage LLM-based agents on service engines.

• Take ownership of the transition of agents from configuration to production.

• Provide support and maintenance for production Triage services through bug fixes, dependency and model upgrades, releases, and operational health management.

• Integrate LLM and generative AI services, including Azure OpenAI, into operational business workflows.

• Implement CI/CD, automated testing, monitoring, and observability for AI services.

• Contribute to the creation of dashboards and alerting systems.

• Operate within architectural standards and review processes.

• Document solutions for ease of operation by others.

• Manage clinical data, including PHI, in accordance with security, privacy, and compliance regulations.

⛳️ Requirements

• Bachelor's degree in Computer Science, Software Engineering, or a related field — or equivalent professional experience.

• 3–5+ years of experience in software engineering.

• Proficient in Python programming.

• Knowledge of at least one additional modern programming language: TypeScript, C#, Java, or Go.

• Experience in building and utilizing RESTful APIs and microservices.

• Familiarity with message-driven and service-bus integration patterns.

• Experience integrating LLM APIs, such as Azure OpenAI, OpenAI, or Anthropic, into applications.

• Background in Agile development environments with code reviews, testing, and CI/CD practices.

• Experience with FHIR, particularly in prior-authorization workflows, PAS implementation guide, X12 278 crosswalk, or other healthcare interoperability (preferred).

• Familiarity with agentic AI frameworks and patterns, such as pydantic-ai or LangGraph, and structured-output LLM development (preferred).

• Experience with LLM observability and telemetry, including OpenTelemetry-based tracing, Logfire, or similar (preferred).

• Knowledge of Azure cloud services, including Azure AI services, Azure SQL, and containerized deployment (preferred).

• Experience with Docker/Kubernetes and infrastructure-as-code methodologies (preferred).

• Previous experience in healthcare, payer, or other regulated engineering domains (preferred).

• Submission of a government-issued photo ID and identity verification during interviews.

• Completion of a comprehensive background check.

• In-person I-9 verification required.

• May be subject to drug screening prior to employment.

• High-speed internet connection of over 10 Mbps is required at home.

🏝️ Benefits

• Work/life balance.

• Flexible work arrangements.

• Autonomy to accomplish tasks effectively.

• Comprehensive benefits, including health insurance, for eligible employees.

• Equal opportunity employer.

• High-speed internet connection of over 10 Mbps is required at home.