Python Developer – Agentic AI Infrastructure (AI/LLM Engineer) - Local/Hybrid

Discover Vanderbilt University Medical Center:  Located in Nashville, Tennessee, and operating at a global crossroads of teaching, discovery, and patient care, VUMC is a community of individuals who come to work each day with the simple aim of changing the world. It is a place where your expertise will be valued, your knowledge expanded, and your abilities challenged. Vanderbilt Health is committed to an environment where everyone has the chance to thrive and where your uniqueness is sought and celebrated. It is a place where employees know they are part of something that is bigger than themselves, take exceptional pride in their work and never settle for what was good enough yesterday. Vanderbilt’s mission is to advance health and wellness through preeminent programs in patient care, education, and research.

Organization:

HealthIT AI Development Solutions

Job Summary:

This role will design, build, and operate production-grade agentic AI solutions and supporting infrastructure using Python. You will develop AI agents and workflows that securely leverage institutional data, systems, and tooling to automate routine technical and operational work, accelerate delivery of AI-enabled capabilities, and enable broader adoption through reusable components and patterns.

This is a hands-on engineering role focused on taking concepts from prototype to production—iterating quickly while meeting enterprise expectations for security, reliability, maintainability, and documentation.

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Key Responsibilities 

• Design and implement agentic AI workflows and services in Python, including tool-using agents, orchestrated multi-step processes, and integration patterns. 

• Build and maintain reusable frameworks/components for agent development (e.g., agent runners, tool registries, prompt/config management, evaluation harnesses). 

• Integrate agents with enterprise data sources and systems in a secure, auditable manner (APIs, services, databases, and internal platforms as applicable). 

• Develop and harden AI-enabled applications and supporting APIs for internal use, including deployments to OpenShift. 

• Implement best practices for production readiness: testing, logging/metrics, error handling, performance considerations, and operational runbooks. 

• Contribute to platform standards and reference implementations for agentic development (including patterns aligned with Model Context Protocol where applicable). 

• Collaborate with stakeholders to translate use cases into technical requirements, iterate on solutions, and deliver measurable outcomes. 

• Ensure appropriate documentation for all development and modifications, including architecture notes and operational guidance. 

• Ensure integrity, confidentiality, and security of institutional data used by AI solutions (data handling, access controls, and policy-aligned implementations). 

Technical Capabilities (What Success Looks Like) 

Agentic AI / LLM Application Development 

• Has built AI/LLM-enabled services beyond experimentation, with production considerations (latency, retries, fallbacks, rate limits, guardrails, and monitoring). 

• Understands agent patterns (tool use/function calling, planning/execution loops, retrieval-augmented workflows, memory/state management, and evaluation). 

 

Python Application Development 

• Delivers clean, testable Python code using modern tooling and best practices (typing, linting/formatting, packaging, dependency management). 

• Able to debug complex issues across services, integrations, and runtime environments. 

 

Systems Integration &am