Full-Stack AI Engineer (AI Service Engines & Integration)

Summary

Evolent partners with health plans and providers to improve outcomes for people with complex and costly health conditions. The Full-Stack AI Engineer will design, build, deploy, and operate AI service engines and integrations, including LLM-based agents, FHIR prior-authorization workflows, and production-grade monitoring and CI/CD. The role also supports existing Triage services and ensures clinical data is handled according to security, privacy, and compliance requirements.

Responsibilities

• Design and build the adaptor layer between AI service engines and the enterprise service bus, including construction and handling of FHIR PAS (Prior Authorization Support) payloads
• Build a new synchronous service engine for real-time AI workloads (e.g., letter generation), adapting the architecture of the existing asynchronous Triage engine
• Build, deploy, and operate LLM-based agents on the service engines; own the mechanics of getting an agent from configuration to production
• Support and maintain the existing production Triage services: bug fixes, dependency and model upgrades, releases, and operational health
• Integrate LLM and generative AI services (Azure OpenAI and related) into production business workflows
• Implement CI/CD, automated testing, monitoring, and observability for AI services; contribute to dashboards and alerting
• Work within the team's architecture standards and review gates; document what you build so others can run it
• Handle clinical data (including PHI) according to organizational security, privacy, and compliance requirements

Skills

• Bachelor's degree in Computer Science, Software Engineering, or a related field — or equivalent experience
• 3–5+ years of software engineering experience
• Strong Python; experience with at least one other modern language (TypeScript, C#, Java, or Go)
• Experience building and consuming RESTful APIs and microservices, including message-driven / service-bus integration patterns
• Experience integrating LLM APIs (e.g., Azure OpenAI, OpenAI, Anthropic) into applications
• Experience working in Agile development environments with code review, testing, and CI/CD
• High speed internet over 10 Mbps and, specifically for all call center employees, the ability to plug in directly to the home internet router
• FHIR experience — especially prior-authorization workflows (PAS implementation guide, X12 278 crosswalk) or other healthcare interoperability (HL7v2, CDA)
• Experience with agentic AI frameworks and patterns (e.g., pydantic-ai, LangGraph, or similar) and structured-output LLM development
• Experience with LLM observability and telemetry (OpenTelemetry-based tracing; Logfire or similar)
• Azure cloud experience (Azure AI services, Azure SQL, containerized deployment)
• Docker/Kubernetes and infrastructure-as-code practices
• Healthcare, payer, or other regulated-domain engineering experience

Qualifications

Must Haves

• Bachelor's degree in Computer Science, Software Engineering, or a related field — or equivalent experience
• 3–5+ years of software engineering experience
• Strong Python; experience with at least one other modern language (TypeScript, C#, Java, or Go)
• Experience building and consuming RESTful APIs and microservices, including message-driven / service-bus integration patterns
• Experience integrating LLM APIs (e.g., Azure OpenAI, OpenAI, Anthropic) into applications
• Experience working in Agile development environments with code review, testing, and CI/CD
• High speed internet over 10 Mbps and, specifically for all call center employees, the ability to plug in directly to the home internet router

Nice to Haves

• FHIR experience — especially prior-authorization workflows (PAS implementation guide, X12 278 crosswalk) or other healthcare interoperability (HL7v2, CDA)
• Experience with agentic AI frameworks and patterns (e.g., pydantic-ai, LangGraph, or similar) and structured-output LLM development
• Experience with LLM observability and telemetry (OpenTelemetry-based tracing; Logfire or similar)
• Azure cloud experience (Azure AI services, Azure SQL, containerized deployment)
• Docker/Kubernetes and infrastructure-as-code practices
• Healthcare, payer, or other regulated-domain engineering experience

Benefits

• Comprehensive benefits, including health insurance benefits, for qualifying employees.
• Work/life balance and flexibility to suit work to their lives.