Jobs → Engineering → AI/ML Engineer

About the Role We are seeking an AI/ML Engineer to build and operate AI agent orchestration services. This role involves developing federation agents and prior authorization orchestrators, implementing agent interoperability, and designing optimized prompts for AI models. Key Responsibilities • Build and operate AI agent orchestration services using AWS Bedrock and AgentCore • Develop federation agents supporting Policy, Provider, and Member domains • Own a prior authorization (PA) orchestrator coordinating approximately 13 sub-agents in parallel, targeting a sub-2-second SLO • Implement agent interoperability using MCP and A2A protocols • Develop agent workflows using LangGraph or equivalent orchestration frameworks • Design and optimize prompts for Claude Sonnet and Opus models • Create AI evaluation frameworks, test cases, and golden datasets • Implement RAG solutions, custom tools, REST APIs, and serverless integrations • Integrate AI/ML solutions with Databricks for enterprise data access, processing, and analytics • Work with Databricks notebooks, Python, SQL, and data pipelines to support AI agent workflows and retrieval use cases • Build secure, scalable services using AWS Lambda, API Gateway, Terraform, DynamoDB, RDS/Aurora, and Step Functions • Implement authentication and security using OAuth 2.0, OIDC, and mTLS • Establish monitoring and observability using CloudWatch, OpenTelemetry, and distributed tracing • Support multi-tenant SaaS architecture and healthcare data privacy requirements, including HIPAA/PHI awareness Requirements • AWS Certified Machine Learning – Specialty or AWS Certified Solutions Architect • Strong Python development skills • Experience with AWS Bedrock, SageMaker, and/or AgentCore • Hands-on experience with AI agent orchestration frameworks such as LangGraph • Knowledge of MCP, A2A, and custom tool development • Experience with Databricks, including notebooks, Python, SQL, and data integration for AI/ML applications • Strong prompt engineering, LLM evaluation, and golden-dataset design experience • Experience with RAG and LLM-powered applications • Experience with REST APIs, AWS Lambda, API Gateway, and Terraform • Familiarity with DynamoDB, RDS/Aurora, and Step Functions • Knowledge of OAuth 2.0, OIDC, mTLS, Git/GitHub, and CI/CD • Experience with CloudWatch, OpenTelemetry, logging, and distributed tracing • Understanding of secure, multi-tenant architectures and HIPAA/PHI requirements