Senior Analyst, AI Engineer at Cardinal Health
Atlanta, GA
$80,500–$103,410from the description
Jul 14, 2026
Atlanta, GA
Jul 21, 2026
What this job asks for AI summary
An early-career engineering role focused on building and deploying generative AI applications on Google Cloud Platform, primarily using Vertex AI and the Gemini model family. Day-to-day work spans constructing RAG pipelines, developing agentic AI systems with tool-use and reasoning loops, managing vector data pipelines, and handling prompt engineering and evaluation. A background in Python and basic cloud familiarity is expected; healthcare domain knowledge is a bonus.
Junior level · 1+ years · Remote · Full-time
“or” means any one of them counts — you don't need all of them.
Posted 15 times — it's one opening, so apply once.
We read this from the posting text with AI. Skim the description below before ruling yourself out.
How this req sits in the market our data
Rare in this occupation — lead with these, and say what you built with them.
Most people in this occupation already list these. Still required — just not what gets you shortlisted.
What the occupation pays Median $138,970 (middle half $107,524–$175,762). This posting is about at that midpoint.
Estimated from BLS employment for this occupation and area, per-skill prevalence across our listing corpus, and published wage benchmarks — as of Jul 28, 2026. It is a model, not a headcount.
Why we read it this way (9)
No work location is specified in the posting — the CBSA and state fields are left blank. Cardinal Health is headquartered in Dublin, OH, but the JD does not name a city or state for this role.
The posting is explicitly framed as an early-career / entry-level role ('ideal for an early-career engineer', '1+ years preferred'), supporting a Junior seniority classification despite the AI Engineer title carrying no explicit level word.
The bachelor's degree is listed as 'preferred', not required, and the posting explicitly encourages candidates without a college degree to apply — degree requirement is therefore None.
The '1+ years of experience preferred' language is also framed as preferred rather than a hard gate; the overall years minimum is set to 1 as the closest stated figure, but this should be read as a soft floor.
GCP sub-services (Cloud Storage, Cloud Run, BigQuery) are listed under a 'Basic familiarity' heading in the tech stack section, which functions as the primary requirements block for this role; they are treated as hard gates at a foundational level.
LangChain, LangGraph, LlamaIndex, and Vertex AI Agent Builder are described as 'highly regarded' — a preference signal, not a hard gate.
TensorFlow, PyTorch, Amazon SageMaker, and Jupyter Notebooks appear in the Qualifications section but are framed as 'a plus' or listed alongside other nice-to-have items; treated as preferred.
Clinical/healthcare domain knowledge is called 'a major plus' and 'prior experience' — treated as preferred.
The alt SOC 15-2051 (Data Scientists) is noted because the role involves embeddings, vector pipelines, RAG, and ML frameworks, though the primary day-to-day work is building and deploying AI applications (software development).
Read the full posting
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