AI-Driven Decision Intelligence Leader

Humana Inc

Annapolis (MD)

Hybrid

USD 129,000 - 178,000

Full time

7 days ago

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Job summary

Humana Inc. seeks a Lead Decision Intelligence Engineer to drive decision intelligence across the NBA platform.

You will translate stakeholder objectives into structured decision models, build agentic workflows, and lead a small team of engineers using LangGraph, LangChain, and Azure OpenAI to improve member engagement. This hands-on role blends decision science, AI engineering, and software architecture, with cross‑functional collaboration across business, product, and engineering teams.

Qualifications

Bachelor's degree in computer science or related field.
6+ years of software engineering, machine learning engineering, AI engineering, or decision intelligence experience, including at least 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, decision automation, objectives, constraints, and outcome measurement.
Experience implementing LLM application patterns including tool calling, structured outputs, retrieval‑augmented generation (RAG), memory management, and workflow orchestration.
Experience building evaluation frameworks for AI systems, including automated evaluation, human review, performance measurement, and experimentation.
Ability to map business processes into formal decision frameworks and communicate those models to both 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

Architect, implement, and operate microservices that deliver: action and variant metadata.
Context‑aware policy and eligibility evaluation.
Versioned, read‑optimized APIs for high‑performance runtime consumption.
Guarantee that services are highly available, with low latency.
Horizontally scalable for increased demand and backward compatible upgrades.
Apply industry best practices for API design, schema evolution, service isolation, and secure integration.
Design, deploy, and maintain resilient database schemas to support action and variant catalogs.
Implement and monitor schema migration, indexing, and data integrity for governance.
Integrate and manage enterprise‑grade rules engines for policy‑driven decisions.
Lead AI‑assisted, agentic engineering initiatives and governance frameworks.
Collaborate with platform, data, and ML teams to maintain integration standards.
Mentor junior engineers and contribute to technical standards.