AI Engineer

Our client is seeking an AI Engineer to support the design, development, validation, and deployment of AI-enabled capabilities across a Revenue Cycle Management (RCM) platform. This role focuses on building production-grade AI systems that improve operational workflows across claims, denials, AR management, coding, and performance analytics. The role includes deploying AI solutions on cloud-native, containerized infrastructure using Kubernetes. Responsibilities:

• Design and deploy AI-enabled workflows for RCM use cases
• Build LLM-based applications including RAG and agent orchestration
• Develop containerized AI services using Docker and Kubernetes (AKS/EKS/GKE)
• Implement CI/CD pipelines for Kubernetes deployments
• Integrate AI with enterprise systems and data pipelines
• Support agent runtime, evaluation frameworks, and human-in-the-loop workflows
• Ensure scalability and reliability of AI services in production, * AI features deployed into live RCM workflows
• Measurable improvements in productivity and throughput
• Scalable AI services operating across Kubernetes environments supporting multiple clients

• Minimum of five (5)+ years of overall work experience
• Experience with LLMs, RAG, and generative AI application development
• Strong Python skills and experience building APIs / backend microservices
• Experience with cloud AI platforms (Azure AI, AWS Bedrock/SageMaker, or GCP Vertex AI)
• Experience integrating AI with data pipelines, ETL/ELT, and enterprise data integration
• Experience with vector databases, embeddings, and semantic search
• Experience with AI/ML model evaluation, validation, monitoring, and production reliability
• Experience with CI/CD and MLOps for production AI systems
• Understanding of AI governance requirements (explainability, auditability, compliance)
• Proven experience delivering AI solutions from prototype to production
• Experience with Docker and Kubernetes (AKS/EKS/GKE) for containerized deployments
• Understanding of container orchestration and scalable system design

Preferred Qualifications:

• Experience in healthcare revenue cycle management (RCM)
• Experience with agent-based orchestration
• Familiarity with MLOps practices
• Experience with Kubernetes tooling such as Helm and service mesh technologies
• Experience with GPU workloads in Kubernetes
• Experience building AI/ML or LLM applications in production environments