Principal Decision Intelligence Engineer

Humana

Confirmed live 2 days ago High trust
Hybrid

Quick summary

Work type
Hybrid
Location
Boston, MA
Salary
$187,900–$258,500 / yr
Posted
56 days ago
Freshness
Confirmed live 2 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $218k
This role $223k
$139k most similar roles pay here $289k

This role pays more than 61% of similar roles. Most pay $184,932–$250,250 — the shaded band above. At the midpoint, this role pays about $223k versus about $218k for comparable roles.

Based on 240 similar postings.

Employer

About Humana

Humana Inc. is a leading American for-profit health insurance company based in Louisville, Kentucky, specializing in Medicare Advantage plans.

Humana currently has 20 open roles on FindRole.

Listed pay typically runs $129,300–$177,800 across 20 roles with salary data.

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View all roles at Humana

At a glance

TL;DR · Principal Decision Intelligence Engineer

The Principal Decision Intelligence Engineer serves as the technical lead for the NBA platform's decision intelligence capabilities. This principal-level role involves end-to-end ownership of the decision system, encompassing feature engineering, optimization logic, scoring, and production deployment. The engineer will design architectures to determine member actions across various channels, translate business objectives into reward structures, and manage the member feature layer on a Databricks Lakehouse using clinical and behavioral signals. Key responsibilities include leading a multi-functional team of engineers, mentoring staff, and overseeing experimental designs for holdout frameworks. Required skills include proficiency in Python, PyTorch, MLflow, and PySpark, along with experience in linear programming or constraint-based optimization. The role addresses the complex problem of determining optimal sequences of actions within a member journey to balance immediate engagement with long-term outcomes in a regulated environment.

What you'll do

  • Own the end-to-end decision pipeline from feature engineering and optimization to production deployment and monitoring.
  • Design the architecture for determining member actions, including reward structures, constraints, and optimization formulations.
  • Build and manage the member feature layer on the Databricks Lakehouse using various behavioral and clinical signals.
  • Lead the design of action sequences across member journeys while balancing short-term engagement with long-term goals.
  • Manage production systems for scoring pipelines, serving infrastructure, and real-time feedback loops from downstream data.
  • Design holdout frameworks and online evaluation strategies to measure the impact of decisioning changes.
  • Lead a team of engineers by conducting design reviews, setting technical standards, and providing mentorship.
  • Champion the integration of AI coding and research tools across the engineering organization.

What we're looking for

  • Bachelor's degree in computer science or a relevant field.
  • 10+ years of experience in software engineering with exposure to data-intensive applications, applied AI, or decision systems.
  • 2-5 years of experience in product people leadership and managing multifunctional technical teams.
  • Strong foundation in optimization, sequential decision-making, and designing reward structures for system optimization.
  • Hands-on experience with Python, backend services, data pipelines, and AI/ML tools like PyTorch or MLflow.
  • Experience building and owning large-scale pipelines on cloud platforms such as Databricks or Snowflake.
  • Strong grounding in experimental design, including constructing clean tests and interpreting results correctly.
  • Fluency with AI productivity tools such as Claude or GitHub Copilot.

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