VP, Product Engineering

Regis University•Plano, TX

3d•Hybrid

About The Position

Take your career to the next level! In the last few years our goal has been expansion, creating growth opportunities for many of our team members. Not only are we serious about growth, but we are also serious about helping our customers during hard financial times. We take pride in providing solutions and offering a helping hand, not only to our customers but also to the communities we serve. As we continue to expand and grow into a national leader in consumer financing, we invite you to consider joining our team. If you're passionate about making a meaningful impact in people's lives and bringing a personal touch to finance, we'd love to have you on board! Job Purpose This senior leadership role sits at the intersection of software product delivery, enterprise data platform development, and AI transformation. You'll lead engineering for consumer-facing and internal software products while building and scaling RMC's Snowflake-based data platform — and you'll serve as a champion for AI adoption, driving the integration of agentic workflows and AI-powered capabilities into everything we build. You'll lead a blended team of onshore and offshore engineers, partnering with Product, Data Science, Operations, Compliance, and Finance to drive measurable business outcomes.

Requirements

10+ years in software engineering; 5+ years leading teams of 10+ including offshore/nearshore
Proven delivery of complex, enterprise-grade software products (cloud-native, microservices, APIs)
Hands-on Snowflake data platform experience: schema design, pipelines, data product development
Strong data engineering tooling: dbt, Kafka event streaming, ELT/ETL, data warehouse architecture, SQL optimization
Agile delivery leadership across multi-team environments
Demonstrated experience integrating AI/LLM capabilities into production software products, including familiarity with agentic patterns (tool use, orchestration, autonomous agents)
Regulated industry experience (financial services preferred) with data governance and security knowledge
Exceptional executive communication skills — including the ability to make the case for AI investment and translate AI concepts for non-technical stakeholders

Nice To Haves

Consumer lending, fintech, or installment finance experience
Hands-on experience with AI agent frameworks (LangChain, LangGraph, AutoGen, or equivalent) and LLM API integration
Microsoft Azure or AWS AI/ML services experience alongside Snowflake
Familiarity with FFIEC, OCC, or CFPB technology and data risk guidance
Bachelor's or Master's in CS, Engineering, Information Systems, or equivalent experience

Responsibilities

Lead architecture, development, and delivery of software products across web, API, and mobile channels
Drive Agile execution across onshore and offshore teams with high delivery velocity and code quality
Establish CI/CD pipelines, automated testing, code review standards, and secure SDLC practices
Collaborate with Product Management and UX to translate roadmap priorities into engineering delivery
Own end-to-end software quality from test strategy through production observability
Champion the design and integration of agentic AI workflows into software products — embedding LLM-powered decisioning, automation, and intelligent assistance directly into the user and operational experience
Own architecture, development, and operations of RMC's enterprise data platform on Snowflake
Build and lead a data engineering team delivering reliable, scalable pipelines for analytics, ML, and reporting
Implement modern data stack practices — dbt, ELT patterns, data contracts, data mesh
Partner with the CDAO to align platform capabilities with enterprise AI/ML and BI needs
Ensure compliance with SOX, GLBA, and CCPA data governance requirements
Serve as a senior advocate for AI adoption across the engineering organization — setting the vision, modeling the behavior, and raising the bar on how teams think about AI-augmented development and delivery
Define and promote engineering patterns for agentic AI workflows: autonomous task execution, multi-step reasoning, tool use, and human-in-the-loop oversight within production systems
Partner with the CDAO and business leaders to identify high-value opportunities to embed AI capabilities into lending products, internal tooling, and operational processes
Establish responsible AI development standards — ensuring agentic systems are explainable, auditable, and compliant with financial services regulatory expectations
Build, mentor, and retain high-performing onshore and offshore engineering teams
Manage vendor and offshore partner relationships with clear delivery and quality standards
Communicate technical vision and delivery status to executive leadership
Contribute to technology strategy, annual planning, and engineering budget