Humana

Senior AI Solutions Architect

Humana

full-time

Posted on:

Location Type: Remote

Location: Remote • California, Illinois, Montana, South Dakota • 🇺🇸 United States

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Salary

💰 $117,600 - $161,700 per year

Job Level

Senior

Tech Stack

AzureCloud

About the role

  • work with user groups to solve business problems with agentic AI.
  • build a world class agentic AI enterprise capability leveraging cloud platforms, analytics, and agile development methodologies.
  • meet with industry experts, reviewing/selecting enterprise technology tools and processes, designing solutions, and getting hands on with the implementation.

Requirements

  • Proven experience working with ML engineering teams and delivering ML-powered systems in production at scale.
  • Understanding of generative AI systems, including hands-on experience working with large language models (LLMs), embeddings, retrieval pipelines, prompt engineering, and evaluation strategies.
  • Strong engineering fundamentals: modern software development practices, cloud-native architectures (preferably in Azure), and ML lifecycle tools.
  • Experience designing AI capabilities or shared services used by multiple product teams.
  • Familiarity with tools like LangChain, LangGraph, LlamaIndex, OpenAI APIs, HuggingFace, Weaviate/FAISS, and vector databases.
  • Experience in regulated industries like healthcare, insurance, or finance.
  • Prior experience standing up developer platforms or internal ML tooling.
  • Excellent communication and collaboration skills—you can translate between technical and business stakeholders and rally others around a shared vision.
Benefits
  • medical, dental and vision benefits
  • 401(k) retirement savings plan
  • time off (including paid time off, company and personal holidays, volunteer time off, paid parental and caregiver leave)
  • short-term and long-term disability
  • life insurance
  • many other opportunities

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard skills
machine learning engineeringgenerative AI systemslarge language modelsembeddingsretrieval pipelinesprompt engineeringevaluation strategiescloud-native architecturesML lifecycle toolsAI capability design
Soft skills
communication skillscollaboration skillsstakeholder managementvision alignment
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