below marketmost similar roles pay hereabove market
This role pays less than
99%
of similar roles. Most pay
$162,000–$231,150
— the blue band above.
At the midpoint, this role pays about
$110k
versus about
$197k
for comparable roles.
Based on 240 similar postings.
Employer
About Cardinal Health
Cardinal Health is a global healthcare services and products company specializing in pharmaceutical distribution, medical products, and supply chain solutions for healthcare providers and pharmacies. Industry: Healthcare Distribution & Services
Cardinal Health currently has
58 open roles
on FindRole.
Listed pay typically runs
$105,100–$152,400
across 29 roles with salary data.
JOB TITLE: AI/ML Engineer
The AI/ML Engineer joins the Data Science team to design and deliver enterprise-scale Generative AI solutions. This role involves partnering with product managers and software engineers to transform business problems into scalable AI applications. Day-to-day responsibilities include developing Large Language Models, Retrieval-Augmented Generation architectures, AI Agents, and intelligent automation workflows. The engineer will build production-grade ML systems, integrate AI capabilities into enterprise platforms, and ensure solutions are secure and measurable. Key technologies include Python, FastAPI, Flask, and Docker, with deployment on Kubernetes and cloud platforms like GCP, Azure, or AWS. Candidates must utilize frameworks such as LangChain, LangGraph, or CrewAI while managing vector databases and relational or NoSQL databases. The work focuses on solving complex business problems by extracting knowledge from large data sets.
Design and deliver enterprise-scale Generative AI solutions including LLMs, RAG, and AI Agents.
Build production-grade ML systems and integrate AI capabilities into existing enterprise platforms.
Transform complex business problems into scalable AI-powered applications and intelligent automation workflows.
Develop and manage REST APIs using frameworks like FastAPI or Flask.
Deploy and manage containerized workloads on Kubernetes platforms using cloud-native architectures.
Implement MLOps and LLMOps practices for model deployment, monitoring, observability, and governance.
Apply security, privacy, and compliance controls to ensure responsible AI usage.
Translate business requirements into technical specifications and provide production support for AI solutions.
What we're looking for
Bachelor's degree in Computer Science, Engineering, Data Science, Artificial Intelligence, or related discipline; equivalent experience considered.
4-8 years of experience in Software Engineering, Machine Learning Engineering, AI Engineering, or related fields (preferred).
Experience designing and implementing Generative AI solutions using Large Language Models like OpenAI, Gemini, Claude, Llama, or Mistral.
Strong understanding of Retrieval-Augmented Generation (RAG) architecture and vector databases.
Experience building AI Agents and multi-agent workflows using frameworks such as LangGraph, LangChain, CrewAI, or Semantic Kernel.
Proficiency in Python and experience developing production-grade applications, REST APIs (FastAPI, Flask), and containerizing applications with Docker.
Experience deploying and managing workloads on Kubernetes platforms and cloud platforms such as GCP, Azure, or AWS.
Knowledge of MLOps/LLMOps, prompt engineering, responsible AI, and integrating AI services through APIs and enterprise systems.