GenAI Engineer — Healthcare AI Solutions

Cardinal Health; Montpelier (VT); On-site; USD 96,000 - 151,000; Full time

Benefits offered by this job

Medical, Dental, Vision

Paid time off

HSA

401k

MyFlexPay

FSAs

Disability

Work-Life resources

Parental leave

Healthy lifestyle programs

Job summary

Cardinal Health’s Sonexus Health Pharmacy Services seeks an AI Engineer to design, deploy, and scale GenAI-powered solutions for healthcare operations and clinical-adjacent workflows. You will collaborate with product, data, and business teams to ensure compliant, secure AI capabilities across enterprise processes.

The role emphasizes agentic workflows, RAG, and production-grade APIs with cloud foundations on Azure and GCP, aligned to HIPAA and PHI handling standards.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field preferred.
• 5+ years of professional software engineering experience, with strong proficiency in Python and any of Java / .Net / C# etc preferred.
• 2+ years of hands-on experience building GenAI / LLM-based applications in real-world or enterprise environments.
• Experience designing and implementing agentic or multi-step AI workflows using orchestration frameworks such as LangGraph or similar.
• Strong understanding of retrieval pipelines, embeddings, vector databases, prompt engineering, and LLM APIs.
• Experience deploying AI solutions in cloud environments (Azure and/or GCP).
• Familiarity with secure application development and enterprise integration patterns.
• Experience working in healthcare, life sciences, pharmacy services, or regulated industries preferred.
• Knowledge of HIPAA, PHI data handling, and secure AI design in compliance-driven environments preferred.
• Exposure to responsible AI practices, model monitoring, and governance in enterprise settings preferred.

Responsibilities

• Design, prototype, and deploy Generative AI applications using techniques such as Retrieval-Augmented Generation (RAG), prompt engineering, fine-tuning, and vector search.
• Build and maintain Python-based APIs and software components to support AI services and ensure scalable, production-grade solutions.
• Develop multi-step, agentic workflows for reasoning, task execution, and orchestration using frameworks such as LangChain, LangGraph, and LlamaIndex.
• Integrate AI capabilities into healthcare and pharmacy services workflows, including case management, program operations, analytics, and internal knowledge systems.
• Deploy, monitor, and optimize GenAI models and pipelines using cloud-native tooling, orchestration frameworks, and MLOps best practices.
• Contribute to the AI platform and reference architecture across cloud environments, including Microsoft Azure and Google Cloud Platform (GCP).
• Collaborate with cross-functional teams to ensure AI solutions meet security, privacy, and compliance requirements (e.g., HIPAA, PHI handling, responsible AI principles).
• Document designs, patterns, and best practices to support enterprise reuse and long-term platform sustainability.
• Evaluate vendor solution architecture, APIs, data flows, identity and access controls, security, scalability, interoperability, and operational supportability.
• Participate in technical discovery and proof-of-concept activities, document findings and trade-offs, and provide recommendations for vendor selection, integration approach, and implementation readiness.

Skills

GenAI / LLMs

Healthcare expertise

AI platform design

Education

Bachelor’s or Master’s degree in CS/AI/ML

Tools

Python

Java

.NET / C#

LangChain

LangGraph

LlamaIndex

Azure

GCP

RAG

Vector databases

Job description

Cardinal Health’s Sonexus Health Pharmacy Services seeks an AI Engineer to design, deploy, and scale GenAI-powered solutions for healthcare operations and clinical-adjacent workflows. You will collaborate with product, data, and business teams to ensure compliant, secure AI capabilities across enterprise processes.

The role emphasizes agentic workflows, RAG, and production-grade APIs with cloud foundations on Azure and GCP, aligned to HIPAA and PHI handling standards.