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.

Duties and Responsibilities

Software Product Engineering:
•⁠ ⁠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

Data Engineering & Platform:
•⁠ ⁠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

AI Evangelism & Enablement:
•⁠ ⁠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

Leadership:
•⁠ ⁠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

Minimum Qualifications

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

Preferred Qualifications

•⁠ 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

Working Conditions

This position works in a hybrid environment.

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