Principal Decision Intelligence Engineer

Overview

Become a part of our caring community. The Principal Decision Intelligence Engineer is the technical lead for the NBA platform's decision intelligence capabilities. This role is responsible for end‑to‑end ownership of the decision system, from member feature signals through optimization and decisioning logic to production deployment.

• Own end‑to‑end delivery of the decision system pipeline from member signals to live decisions, including feature engineering, decisioning logic, optimization, scoring, deployment into the NBA platform, and production monitoring.
• Design the decision intelligence architecture that determines what to do for each member, when, and through which channel, translating business objectives into reward structures, constraints, and optimization formulations.
• Design and build the member feature layer on the Databricks Lakehouse, ensuring signals are available, correct, and timely at decision time.
• Lead the planning and optimization of action sequences across a member journey, balancing short‑term engagement with long‑term outcome goals using reward shaping, constraint satisfaction, policy evaluation, and delayed feedback reasoning.
• Own how decision outputs flow into live systems: scoring pipelines, serving infrastructure, action masking, and real‑time feedback loops from downstream behavioral signals.
• Design holdout frameworks and online evaluation strategies that isolate the effect of decisioning changes, define success metrics, and translate experiment results into system improvements and roadmap input.
• Lead and mentor a multifunctional engineering team across the delivery lifecycle, running design reviews, setting technical quality standards, and ensuring on‑time delivery.
• Champion the use of AI coding and research tools and model high‑leverage AI‑augmented engineering practices.

• Bachelor’s degree in computer science or a relevant field.
• 10+ years of software engineering experience with substantial exposure to data‑intensive applications, applied AI, or decision systems.
• 2‑5 years of product people leadership and experience leading a multifunctional technical team.
• Strong foundation in optimization and sequential decision‑making, including objective functions, constraints, tradeoffs across time, and system design impact.
• Experience designing reward structures, evaluation criteria, or planning frameworks that translate business goals into something a system can optimize against.
• Hands‑on experience with Python and the full engineering stack, including backend services, data pipelines, and AI/ML tooling such as PyTorch, MLflow, PySpark, or equivalents.
• Experience building and owning pipelines on a cloud data platform such as Databricks or Snowflake at scale.
• Strong grounding in experimental design, including constructing clean tests, avoiding confounding, and interpreting results correctly.
• Ability to make independent architectural decisions on complex, ambiguous problems.
• Passionate about improving consumer experiences and strong communication skills across technical and non‑technical audiences.
• Fluency with AI productivity tools (Claude, Git Hub Copilot, or similar).
• Hybrid work in Boston, MA with occasional travel to Humana’s onsite hub as required.

• Master’s degree.
• Experience with linear programming, integer programming, or constraint‑based optimization in a production setting.
• Background in personalization, recommendation systems, or next‑best‑action platforms.
• Familiarity with Kafka‑based event pipelines and real‑time feedback loop design.
• Experience with causal inference or uplift modeling.
• Background in healthcare, insurance, or regulated industries with PHI/HIPAA constraints.

It is the policy of Humana not to discriminate against any employee or applicant for employment because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, marital status, genetic information, disability or protected veteran status. It is also the policy of Humana to take affirmative action, in compliance with Section
503 of the Rehabilitation Act and VEVRAA, to employ and to advance in employment individuals with disability or protected veteran status, and to base all employment decisions only on valid job requirements.