Generative AI Engineer for Enterprise AI Apps

Cardinal Health; Carson City (NV); On-site; USD 95,000 - 122,000; Full time

Benefits offered by this job

Medical, dental and vision coverage

Paid time off

Health savings account (HSA)

401k savings plan

MyFlexPay access to wages

FSAs

Disability coverage

Work-Life resources

Paid parental leave

Healthy lifestyle programs

Job summary

Cardinal Health is seeking an AI/ML Engineer to design and deliver enterprise-scale Generative AI solutions. You will partner with product managers, software engineers, data engineers, and stakeholders to translate business problems into scalable AI applications.

The role involves building production-grade ML systems, deploying AI capabilities across enterprise platforms, and ensuring secure, reliable, and measurable outcomes throughout the full AI product lifecycle.

Qualifications

• Bachelor's degree in Computer Science, Engineering, Data Science, AI or related field; equivalent experience considered.
• Strong proficiency in Python and experience developing production-grade applications.
• Experience building REST APIs using frameworks such as FastAPI, Flask, or similar technologies.
• Experience working within Agile and SDLC frameworks.
• Experience using GitHub and CI/CD platforms.

Responsibilities

• Design and deliver enterprise-scale Generative AI solutions.
• Hands-on development of AI-powered applications, including LLMs, RAG, AI Agents and automation workflows.
• Build production-grade ML systems and integrate AI capabilities into enterprise platforms.

Skills

Python

REST APIs

Docker

Kubernetes

GCP

AWS

Azure

CI/CD

GitHub

LangChain

RAG

OpenAI

LangGraph

Prompt engineering

Production-grade software

Education

Bachelor's degree in Computer Science or related

Tools

FastAPI

Flask

GitHub Actions

Azure DevOps

Jenkins

Kubernetes

GKE

AKS

EKS

Job description

Cardinal Health is seeking an AI/ML Engineer to design and deliver enterprise-scale Generative AI solutions. You will partner with product managers, software engineers, data engineers, and stakeholders to translate business problems into scalable AI applications.

The role involves building production-grade ML systems, deploying AI capabilities across enterprise platforms, and ensuring secure, reliable, and measurable outcomes throughout the full AI product lifecycle.