Captive auto finance platform serving GM dealers across North America, Latin America, and China
GM Financial is General Motors' wholly owned auto finance subsidiary, serving over 9,000 employees across retail lending, lease origination, and dealer commercial credit. The tech stack is split between Azure and AWS with heavy investment in cloud infrastructure (VPC, Transit Gateway, Direct Connect), paired with active adoption of GitHub Copilot and Power Platform — signaling modernization of legacy finance operations. Engineering hiring (90 roles) and a large data cohort (38 roles) reflect active work on an enterprise data lakehouse, vendor risk assessment, and CI/CD maturation, while security (38 roles) tracks third-party risk management and compliance gaps that appear consistently in stated pain points.
Notable leadership hires: Incident Response Lead, Operational Excellence Lead
GM Financial originates and services auto loans, leases, and dealer financing across North America, Latin America, and China. The company operates a traditional captive-finance model: funding retail customers through GM dealer relationships, managing dealer inventory financing, and offering protection products (insurance). Scale runs to 9,000+ employees with headquarters in Fort Worth, Texas. Core challenges center on integrating legacy credit and origination systems with modern CRM platforms, ensuring credit performance monitoring accuracy, and managing third-party risk — all reinforced by active hiring in engineering, data, and security. Recent project work includes front-line contact center implementation, dealer originations experience redesign, and a target operating model transformation.
Primary: C#, Azure (API Management, DevOps, Monitor), AWS (KMS, Organizations, Control Tower). Data: SQL, SAS, Python. Analytics: Power BI, Salesforce. Adopting: GitHub Copilot, Power Platform, Copilot Studio.
Enterprise data lakehouse, vendor risk assessment program, CI/CD pipeline development, front-line contact center for protection products, dealer originations customer experience redesign, and controlled experiments design for model integrity.
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