Senior Analyst, AI Engineer

Cardinal Health

4d•$80,500 - $103,410

About The Position

At Cardinal Health's Artificial Intelligence Center of Excellence, we're focused on using technology to improve healthcare. Our commitment to innovation, design, and a product-centric approach helps us create solutions that make a real difference. We're a team of passionate individuals who thrive in a culture of collaboration and continuous learning. We leverage cutting-edge technology and data insights to solve complex problems, forge new business models, and create products that truly impact the lives of our customers. As an AI Engineer, you will play a key role in building, testing, and deploying cutting-edge artificial intelligence solutions natively on Google Cloud Platform (GCP). Working closely with senior engineers, you will leverage Vertex AI to integrate Large Language Models (LLMs), build Retrieval-Augmented Generation (RAG) pipelines, and develop Agentic AI systems (equipping Gemini models with tools, API access, and reasoning loops). This role is ideal for an early-career engineer who has strong Python skills, a solid grasp of foundational cloud principles, and a passion for building next-generation action-oriented AI.

Requirements

Strong proficiency in Python and standard SQL.
Experience or projects utilizing Google Cloud Platform (e.g., Cloud Storage, Cloud Run, BigQuery).
Basic exposure to Vertex AI Studio, Model Garden, Gemini APIs, or Vertex AI Vector Search.
Conceptual understanding of LLM prompt engineering, embeddings, and agentic workflows.
Comfort with Git, VS Code/Jupyter, and writing clean, modular Python code.
Bachelor’s degree in mathematics, Statistics, Engineering, Computer Science, other related field, or equivalent years of relevant work experience is preferred.
1+ years of experience preffered
Knowledge of Machine Learning and related technologies such as Tensorflow Python, Torch, Amazon SageMaker, Jupiter Notebooks, git.
Understanding of cloud data engineering and integration concepts.
Strong mathematical and statistical skills.
Experience with Google Cloud Platform.
Knowledge of software solutions such as data warehouses and integration platforms.
Knowledge of Agile development skills and experience.

Nice To Haves

Experience or projects utilizing Google Cloud Platform (e.g., Cloud Storage, Cloud Run, BigQuery).
Basic exposure to Vertex AI Studio, Model Garden, Gemini APIs, or Vertex AI Vector Search.
Conceptual understanding of LLM prompt engineering, embeddings, and agentic workflows (experience with Python frameworks like LangChain, LangGraph, LlamaIndex, or Vertex AI Agent Builder is highly regarded).
Knowledge of clinical domain and datasets is a major plus
Experience in Generative AI, RAG implementation, re-ranking, vector db, embeddings etc. is a plus
Prior experience in Healthcare industry and knowledge of clinical data.

Responsibilities

Help build and configure GenAI applications utilizing the Vertex AI SDK and the Gemini model family.
Assist in building AI agents. This includes setting up Vertex AI Extension calls, defining function schemas for Gemini tool-use, and managing agent memory/reasoning loops.
Support the ingestion of unstructured enterprise data into Vertex AI Vector Search or BigQuery to power RAG and grounding mechanisms.
Design, test, and iterate on system instructions. Use Vertex AI's evaluation tools to check for response accuracy, safety, and hallucinations.
Assist in deploying and hosting lightweight AI APIs, agent endpoints, or microservices using Cloud Run or Cloud Functions.
Monitor and debug agent execution paths and API latency using Google Cloud Logging and Cloud Trace.
Actively research and stay up-to-date with the rapidly evolving GenAI landscape, bringing fresh ideas, open-source frameworks, and tools to the team.