Enterprise GenAI & LLM Engineer

Cardinal Health

Annapolis (MD)

On-site

USD 96,000 - 124,000

Full time

9 days ago

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Benefits offered by this job

Medical, dental and vision
Paid time off
HSA
401k plan
Wages access before pay day
FSAs
Disability coverage
Work-Life resources
Paid parental leave
Wellness programs

Job summary

Cardinal Health is seeking an AI/ML Engineer to partner with product managers, software engineers, data engineers and business stakeholders to design and deliver enterprise-scale Generative AI solutions. You will work hands-on on LLMs, RAG, AI Agents and intelligent automation, building production-grade AI applications within secure, scalable cloud-native architectures.

The ideal candidate brings strong software engineering fundamentals, cloud experience and a track record of delivering

Qualifications

  • Experience designing Generative AI solutions with LLMs (OpenAI, Gemini, Claude, Llama, etc.).
  • Strong knowledge of Retrieval-Augmented Generation (RAG) and vector databases.
  • Experience building AI Agents and multi-agent workflows.
  • Experience integrating AI services via APIs and enterprise systems.

Responsibilities

  • Hands-on development of enterprise-scale AI-powered applications.
  • Build production-grade ML systems and secure, reliable cloud-native solutions.
  • Design, deploy and monitor AI workloads across platforms.
  • Collaborate with product managers, software engineers and stakeholders to translate problems into AI solutions.

Skills

Python
REST APIs
GitHub CI/CD
Docker
Kubernetes
Cloud platforms
Software engineering

Education

Bachelor's degree in CS/Engineering/DS/AI

Tools

FastAPI
Flask
LangGraph
LangChain
CrewAI
Semantic Kernel

Job description

Cardinal Health is seeking an AI/ML Engineer to partner with product managers, software engineers, data engineers and business stakeholders to design and deliver enterprise-scale Generative AI solutions. You will work hands-on on LLMs, RAG, AI Agents and intelligent automation, building production-grade AI applications within secure, scalable cloud-native architectures.

The ideal candidate brings strong software engineering fundamentals, cloud experience and a track record of delivering

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