Lead Decision Intelligence Engineer - AI

Humana Inc; Santa Fe (NM); Hybrid; USD 129,000 - 178,000; Full time

Benefits offered by this job

Remote/Hybrid work

Travel for training

Competitive compensation

Job summary

Humana Inc. is seeking a Lead Decision Intelligence Engineer to own production-grade decision intelligence across the NBA platform.

You will translate business objectives and policies into formal decision models and design agentic workflows using LangGraph, LangChain, and enterprise AI tools. Lead a small team of engineers, collaborate with product, decision science, and data teams, and establish governance, testing, and safety patterns for healthcare AI.

Qualifications

• Bachelor's degree in computer science or a related field.
• 6+ years of software or AI engineering experience.
• 1–2 years in technical leadership.
• Strong Python development experience.

Responsibilities

• Model and formally model business decision processes for member engagement.
• Lead production agent workflows with LangGraph and LangChain.
• Collaborate with product, decision science, data science and engineering teams.
• Define governance, safety, and auditability for healthcare AI systems.
• Mentor a small team of AI engineers and establish engineering standards.
• Design and maintain scalable microservices and data schemas.
• Integrate with enterprise AI platforms (Azure/OpenAI, etc.).
• Evaluate AI system performance and conduct experiments.

Skills

Python

Decision intelligence

Technical leadership

Communication

Education

Bachelor's degree in computer science or related field

Tools

LangGraph

LangChain

Azure OpenAI

Azure AI Foundry

Databricks

Job description

Humana Inc. is seeking a Lead Decision Intelligence Engineer to own production-grade decision intelligence across the NBA platform.

You will translate business objectives and policies into formal decision models and design agentic workflows using LangGraph, LangChain, and enterprise AI tools. Lead a small team of engineers, collaborate with product, decision science, and data teams, and establish governance, testing, and safety patterns for healthcare AI.