Digital Technology Lead – Vin & Catalog Modernization

International Motors, LLC•Lisle, IL

21h•Onsite

About The Position

As the Digital Technology Lead for the Vin POD, you are the "Data Architect" of our proprietary vehicle intelligence. You will oversee the technical migration of legacy catalog logic into a modern, scalable microservice environment that supports our global eCommerce goals. You are a "Data-First Engineer" who excels at refactoring legacy codebases into clean, API-first solutions. Your mission is to ensure that our Vin lookup service is the fastest and most accurate in the industry.

Requirements

Bachelor's degree and at least 5 years of software engineer experience
At least 1 years of lead experience
OR
Master's degree and at least 3 years of software engineer experience
At least 1 years of lead experience
OR
At least 8 years of software engineer experience
At least 1 years of lead experience
Qualified candidates, excluding current employees, must be legally authorized on an unrestricted basis (US Citizen, Legal Permanent Resident, Refugee or Asylee) to be employed in the United States.
We do not anticipate providing employment related work sponsorship for this position (e.g., H-1B status)

Nice To Haves

7+ years of professional software engineering, with at least 3 years focused on Data-intensive applications or Legacy Modernization.
Expert-level proficiency in Modern Backend Languages (Node.js/TypeScript, Python, or similar) and Cloud-native Databases.
A proven track record of migrating legacy "monolith" logic into microservices.
Advanced ability to use AI-driven coding assistants to perform "Legacy-to-Modern" code translation and documentation at 10x speed.
Experience with Elasticsearch, Algolia, or similar high-performance indexing tools.
Expert understanding of caching strategies and database query optimization.

Responsibilities

Lead the technical execution of the "Strangler Pattern" migration, moving legacy SQL-based catalog logic into a modern, decoupled microservice (Node.js, .NET, or Java).
Optimize the indexing and query logic for our part-search engine to ensure sub-second response times for complex Vin lookups.
Define and maintain the API contracts that allow the Storefront and Core Commerce PODs to consume fitment and catalog data.
Design and maintain the data structures required for complex part relationships (Supersessions, Alternates, and Kits).
Ensure the new modern services maintain a secure and performant bridge to legacy data sources during the transition phase.
Mastery of AI coding assistants (e.g., GitHub Copilot, Cursor) to rapidly analyze legacy code and "rewrite" it into modern, documented microservices.
Utilize AI agents to automate the categorization of "Unstructured" part data and technical specifications from old manuals.
Leverage AI to generate thousands of Vin-to-Part validation tests to ensure migration doesn't break fitment accuracy.