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Financial Workflow Platform

Graph lifecycle & GoRules engine for insurance financial decisions

Software Engineer (PPO) — Care Health Insurance·Jul 2025 — Present·2 min read

-40%

Deploy time

GoRules + Graph

Rule engine

Full SDLC

Ownership

Problem

Care Health Insurance needed a production-grade system to manage financial decision workflows — rules that determine premiums, approvals, and business-critical calculations. Hardcoded logic was slow to change, risky to deploy, and inaccessible to non-engineering teams.

Constraints

  • Business-critical — Financial decisions affecting core insurance operations
  • Non-technical users — Product and analytics teams need to configure rules without code
  • Safe rollouts — Rule changes must be simulated, reviewed, and approved before production
  • Real-time state — Graph structures update live with complex state management requirements

Architecture

A complete graph lifecycle management system covering creation, versioning, simulation, execution, and approval:

  1. Graph Engine — Rule graphs with branching logic, conditional paths, and deterministic execution
  2. GoRules Integration — JDM Editor + Zen Engine for no-code business rule configuration
  3. Approval Workflows — Draft approval with diff visualization for safe production deployments
  4. Configuration-Driven Backend — Dynamic systems eliminating hardcoded logic
  5. API Layer — RESTful endpoints with validation, authorization, and audit logging
  6. SIGMA Premium Calculation Engine — Shipped frontend for premium calculation to production
ADR

GoRules Decision Engine over custom rule parser

GoRules provides a battle-tested JDM format, visual editor, and Zen Engine runtime. Non-technical teams can configure rules while engineers control the integration layer.

Alternative considered: Custom DSL — full control but months of editor and runtime development

Before / After

Key Contributions

  • Designed and implemented complete graph lifecycle management system
  • Integrated GoRules Decision Engine (JDM Editor + Zen Engine)
  • Built configuration-driven backend systems for scalable functionalities
  • Implemented draft approval workflows with diff visualization
  • Solved complex state management for real-time graph updates
  • Shipped SIGMA Premium Calculation Engine frontend to production
  • Owned full SDLC: design docs, implementation, testing, deployment, monitoring

What I'd Do Differently

  • Earlier stakeholder access to simulation — Backend capabilities preceded self-serve testing UI
  • Per-version canary metrics — Would catch edge-case regressions faster during rule rollouts
  • Graph schema registry from day one — Schema drift caused downstream integration friction