AI Engineer – GenAI Application Development

Our team members are at the heart of everything we do. At Cencora, we are united in our responsibility to create healthier futures, and every person here is essential to us being able to deliver on that purpose. If you want to make a difference at the center of health, come join our innovative company and help us improve the lives of people and animals everywhere. Apply today!

About the Role We are seeking a hands-on AI Engineer to build and ship Generative AI applications — from LLM-powered features and RAG pipelines to production-grade AI agents. This is an engineering-focused role centered on writing high-quality software, building AI apps end-to-end, and deploying them reliably to production. You will work closely with the AI Architect and product stakeholders to turn architectural designs into working, tested, deployed systems.

Build and deploy LLM-powered applications, RAG pipelines, and AI agents using Python. Implement retrieval-augmented generation systems: chunking, embeddings, vector search, hybrid retrieval, and re-ranking. Develop AI agents using agentic frameworks (LangChain, LangGraph, CrewAI) under architectural guidance. Build and maintain REST APIs (FastAPI or Flask) that expose AI functionality to applications and services. Take AI solutions from proof-of-concept to production: containerize (Docker), deploy, and monitor. Implement LLM evaluation and testing (Ragas, LangSmith, or custom eval harnesses) to catch regressions and hallucinations. Apply LLMOps/MLOps practices: CI/CD pipelines, prompt/version management, automated testing, and monitoring of latency, cost, and quality. Write clean, maintainable, well-tested software following solid engineering fundamentals. Collaborate with architects, engineers, and product owners to translate designs into working software. Our Tech Stack Databricks — Unity Catalog, Delta Lake, Databricks Apps, and Databricks AI Gateway for model routing and governance. Microsoft Azure, including Azure AI Foundry for model deployment and orchestration. Multi-LLM provider access — Anthropic Claude, OpenAI (GPT & Codex), and other foundation models. ployment.

Bachelor's degree in Computer Science, AI/ML, or a related field (or equivalent practical experience). 5+ years of software engineering experience, including 2+ years hands-on with GenAI / LLM-based applications. Strong Python programming skills and solid software engineering fundamentals. Practical experience building RAG pipelines: embeddings, vector databases (Pinecone, Weaviate, FAISS, ChromaDB, pgvector), and prompt engineering. Experience with at least one agentic / orchestration framework (LangChain, LangGraph, CrewAI, or similar). Experience building and deploying REST APIs (FastAPI or Flask). Familiarity with containerization and deployment (Docker; basic Kubernetes a plus). Working knowledge of at least one cloud platform (Azure, AWS, or GCP) for AI workload deployment. Comfortable working in fast-paced environments and shipping iteratively.

Experience with LLM evaluation frameworks (Ragas, LangSmith, DeepEval, or custom benchmarks). Exposure to Kubernetes, CI/CD pipelines, and production monitoring/observability tools. Experience with SQL / NL-to-SQL pipelines or structured-data integration for AI apps. Familiarity with MCP (Model Context Protocol) or building tool-calling agents. Prior experience taking AI features from POC through full production ownership. HEALTHCARE DOMAIN PREFERENCE We strongly prefer candidates who bring healthcare knowledge alongside their AI/software engineering skills. Our AI applications run on healthcare distribution and specialty pharmacy data — hands-on experience with healthcare distribution data, pharmacy/NDC-level data, or healthcare EMR/EHR systems (HL7, FHIR, claims) is a strong plus. What Cencora offers We provide compensation, benefits, and resources that enable a highly inclusive