Senior Decision Intelligence Engineer

Location: Remote nationwide in the United States; remote/hybrid work is available, with Boston, MA preferred. Occasional travel to hirify.global offices for training or meetings may be required.

Salary: $106,900–$147,000 per year, plus eligibility for a bonus incentive plan.

Company

hirify.global is a U.S. healthcare and health insurance company serving millions of members through hirify.global insurance services and CenterWell healthcare services.

What you will do

• Build, deploy, and operate machine learning and decisioning pipelines for the NBA Decision Intelligence Platform.
• Develop production workflows for feature engineering, model scoring, monitoring, optimization, and MLOps.
• Design decision systems that select appropriate actions while respecting clinical eligibility, suppression rules, channel constraints, program goals, and operational capacity.
• Collaborate with ML engineers, data engineers, platform engineers, product owners, and decision engine teams.
• Deliver reliable, scalable, and auditable systems serving large user populations under production load.

Requirements

• Bachelor’s degree in computer science or a related field.
• At least 5 years of post-undergraduate software engineering or quantitative research experience building and operating large-scale production systems; the role also specifies at least 2 years of post-graduate experience.
• At least 2 years of hands-on production experience with reinforcement learning, operations research, or simulation-driven decision systems.
• Deep knowledge of Markov decision processes, Bellman-equation-based value estimation, reward shaping, exploration-exploitation tradeoffs, and constraint formulation.
• Proficiency in Python and experience with PyTorch or TensorFlow, Ray RLlib or equivalent distributed computation frameworks, Databricks, PySpark, Delta Lake, and MLflow.
• Must be able to work remotely within the United States; a dedicated workspace is required to protect member PHI and HIPAA information.

Nice to have

• Experience with multi-agent reinforcement learning, PettingZoo, or multi-agent simulation and coordination.
• Knowledge of linear programming, mixed-integer programming, Lagrangian relaxation, or constraint programming.
• Experience operating decision or optimization systems in regulated healthcare, finance, or insurance environments.
• Experience with Gymnasium, SimPy, AnyLogic, event-driven feedback loops, or OpenTelemetry instrumentation.

Culture & Benefits

• Remote or hybrid work with typical Monday–Friday business hours and a 40-hour work week.
• Medical, dental, and vision coverage.
• 401(k) retirement savings plan.
• Paid time off, company and personal holidays, and paid parental and caregiver leave.
• Short- and long-term disability coverage, life insurance, and other wellness benefits.

Hiring process

• Initial application prescreen.
• On-demand HireVue assessment with predetermined questions, expected to take approximately 10–15 minutes.
• Subsequent interviews for candidates who advance after assessment review.