We are seeking a Senior Drools Engineer to design, build, and maintain business rules for a large‑scale underwriting and decisioning platform. This role focuses on translating complex credit and risk policies into high‑performance, explainable Drools rules that power real‑time decisions.
Key Responsibilities
• Design, develop, and maintain Drools (KIE) rules using DRL, Decision Tables, and Rule Templates to implement complex underwriting, eligibility, and policy logic
• Optimize rule execution for low latency and high throughput, including management of rule salience, agenda groups, rule flows, and conflict resolution
• Ensure decisions are deterministic, explainable, and auditable, meeting regulatory and audit requirements
• Contribute to the overall decisioning and rules architecture, designing rule sets for reusability, versioning, and controlled rollout
• Participate in design reviews and technical discussions related to rule design and platform evolution
• Develop unit tests and scenario‑based tests to validate rule behavior across multiple decision paths
• Troubleshoot production issues related to rule execution and support deployments across development, QA, and production environments
• Act as a subject‑matter expert for Drools and business rules best practices, mentoring junior engineers
• Establish and enforce standards for rule authoring, documentation, testing, and maintainability
Required Qualifications
• 7+ years of software engineering experience
• 5+ years hands‑on experience with Drools / KIE
• Strong proficiency in Java
• Experience in building a lightweight orchestration layer using Apache Pekko is a plus
• Deep experience with:
◦ DRL, Decision Tables, Rule Templates
◦ Stateless and stateful KIE sessions
◦ Rule performance tuning and debugging
◦ Experience building or supporting policy‑driven or decisioning systems
◦ Strong understanding of business rules management systems (BRMS)
◦ Exposure to cloud platforms and CI/CD pipelines
What Success Looks Like
• Business policies are accurately captured as maintainable Drools rules
• Decisions are fast, consistent, and explainable
• Rule changes can be made confidently without impacting platform stability
• The rules layer is reliable, scalable, and regulator‑ready