Generative AI Engineer for Enterprise ML

Cardinal Health; Denver (CO); On-site; USD 96,000 - 124,000; Full time

Benefits offered by this job

Medical, dental and vision coverage

401k savings plan

Paid time off

Job summary

Cardinal Health is seeking an AI/ML Engineer to partner with product and engineering teams to design and deliver enterprise-scale Generative AI solutions. You will build production-grade AI applications, including LLMs, RAG, AI agents, and orchestration workflows across cloud platforms.

The role requires strong software engineering fundamentals, cloud experience, and a focus on secure, reliable, and measurable AI deployments across the enterprise.

Qualifications

• Design and deliver enterprise-scale Generative AI solutions.
• Hands-on development of AI-powered applications and LLMs.
• Build production-grade ML systems and secure, reliable deployments.
• Collaborate with product managers and engineers to translate business problems into AI solutions.
• Experience with cloud-native architectures and MLOps concepts.

Responsibilities

• Build and deploy AI-powered applications for enterprise platforms.
• Develop and maintain AI workflows, agents, and RAG solutions.
• Collaborate with cross-functional teams to implement secure AI systems.
• Monitor, evaluate and optimize AI models in production.

Skills

Python programming

REST APIs

Agile / SDLC

CI/CD

Docker

Kubernetes

Cloud platforms (GCP/AWS/AZURE)

Generative AI / LLMs

RAG architectures

AI agents / LangChain

Education

Bachelor's degree in CS/Engineering/Data Science/AI

Tools

FastAPI

Flask

GitHub Actions

GitHub

Azure DevOps

Jenkins

Kubernetes

OpenShift

Job description

Cardinal Health is seeking an AI/ML Engineer to partner with product and engineering teams to design and deliver enterprise-scale Generative AI solutions. You will build production-grade AI applications, including LLMs, RAG, AI agents, and orchestration workflows across cloud platforms.

The role requires strong software engineering fundamentals, cloud experience, and a focus on secure, reliable, and measurable AI deployments across the enterprise.