Position Summary: This role will be responsible for developing secure, compliant AI infrastructure and reusable frameworks that enable internal teams and external consultants to build and deploy AI agents for Operations, Human Resources, Admissions, and IT, while also supporting advanced LLM-driven clinical and client risk use cases integrated with Beacon's EHR, eMAR, HRIS, CRM, and incident management systems.

Primary Responsibilities: • Always be compliant with all company and regulatory policies and procedures. AI Agent Platform & Framework Development • Design and maintain an enterprise AI Agent framework supporting: • Task automation • Data retrieval and summarization • Workflow orchestration • Human-in-the-loop approvals • Build shared services including: • Prompt management and versioning • Tool and API integration layers • Authentication, role-based access, and audit logging • Enable safe agent execution with guardrails, validation layers, and escalation paths.

LLM Engineering & MLOps • Implement and manage LLM integrations including: • Secure prompt pipelines • Retrieval-Augmented Generation (RAG) using enterprise data • Model evaluation and drift monitoring • Deploy AI services using scalable cloud-native architecture (APIs, containers, CI/CD). • Optimize performance, cost, and latency across production AI workloads. Data Integration & Platform Collaboration • Work with Data Engineering to leverage: • Microsoft Fabric • Azure Data Lake • Power BI semantic models • Integrate data from: • EHR and eMAR platforms • HRIS and payroll systems • CRM and Admissions platforms • Incident and Quality Management systems

AI Strategy & Continuous Improvement • Contribute to Beacon's enterprise AI roadmap and standards. • Evaluate emerging AI tools, agent frameworks, and healthcare models. • Recommend architecture and vendor platforms to support scalable AI adoption.

Education and Qualifications: • Bachelor's degree in Computer Science, Engineering, Data Science, or related field. • 5+ years of experience in software engineering, data engineering, or AI engineering. • Hands-on experience with: • LLM APIs and orchestration frameworks • Prompt engineering and RAG architectures • API and microservice development • Strong proficiency in Python and modern backend frameworks. • Experience deploying cloud-native services using Docker and CI/CD pipelines. Must pass criminal background checks, central registry check (in applicable states) and child abuse registry (in applicable states).

Travel: Travel is not required.