Lead Decision Intelligence & AI Systems Engineer

Humana Inc

Salem (OR)

On-site

USD 150,000 - 230,000

Full time

9 days ago

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Job summary

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

You will model business decisions, design agentic workflows, and lead a small team of engineers to deliver measurable value through AI-driven member engagement. You will collaborate with business, product, and engineering teams to deploy LangGraph, LangChain, and Azure OpenAI within Humana's AI Gateway, enabling explainable recommendations, action authoring, and

Qualifications

Bachelor's degree in computer science or related field.
6+ years of software engineering, ML engineering, AI engineering, or decision intelligence experience with 1–2 years in a technical leadership capacity.
Strong Python engineering experience building and operating production AI systems.
Hands-on experience building agentic applications using LangGraph, LangChain, AutoGen, CrewAI, or similar orchestration frameworks.
Experience integrating Azure OpenAI, Azure AI Foundry, Vertex AI, Anthropic, OpenAI, or comparable enterprise AI platforms.
Strong understanding of Decision Intelligence concepts including decision modeling, optimization, and outcome measurement.
Experience implementing LLM application patterns including tool calling, retrieval-augmented generation, memory management, and orchestration.
Ability to map business processes into formal decision frameworks and communicate those models to technical and non-technical stakeholders.
Demonstrated ability to lead a small engineering team while remaining a hands-on contributor.
Strong communication skills with the ability to explain complex AI and decision architectures to senior leadership.

Responsibilities

Decision intelligence modeling — analyze and formally model decision processes.
Decision decomposition — break complex processes into decision graphs and optimization opportunities.
Optimization strategy — determine where rules, models, or agentic systems create value.
Agentic workflow delivery — design production agent workflows with multi-agent collaboration.
Knowledge and retrieval systems — design retrieval-augmented architectures for reliable decision context.
LLM and agent engineering — integrate with Azure OpenAI and enterprise models via Humana's AI Gateway.
Reinforcement learning integration — operationalize RL and decision optimization; scale governance.
Evaluation and experimentation — build rigorous evaluation frameworks for AI systems.
AI governance and safety — implement guardrails, observability, and compliance.
Team leadership — mentor AI engineers and enforce engineering standards.
Cross-functional partnership — work with product, decision science, and data science teams.