Pennymac is looking to scale its engineering organization and modernize its mortgage-focused fintech platform by defining and executing a cohesive technology strategy, driving modernization, scalability, and automation through cloud-native architecture on AWS, and championing the adoption of AI-enhanced engineering workflows.
Requirements
- Expertise in: js, Python, and TypeScript
- Expertise in: Modern frontend frameworks (e.g., React, Next.js)
- Expertise in: AWS cloud architecture (Lambda, API Gateway, DynamoDB, RDS, etc.)
- Expertise in: AI-enhanced development environments (e.g., Cursor, Devin, GitHub Copilot, Replit)
- Strong understanding of microservices, event-driven architecture, REST/GraphQL APIs, and data privacy controls.
- Deep understanding of U.S. mortgage processes: borrower onboarding, loan origination, underwriting, pricing, secondary market delivery.
- Experience integrating with third-party lending systems such as Encompass, Blend, ICE, MERS, or proprietary loan origination software.
Responsibilities
- Define and own the enterprise-wide technology roadmap in alignment with business priorities and regulatory obligations in the mortgage space.
- Drive modernization, scalability, and automation through cloud-native architecture on AWS.
- Lead full-stack engineering teams working across Python, TypeScript, and cloud services.
- Ensure delivery of scalable, secure, and high-performance systems for origination, underwriting, eClosing, and loan delivery pipelines.
- Oversee architecture reviews, design decisions, and implementation of mission-critical services.
- Drive adoption of AI copilots and automation to streamline development, code review, test writing, and documentation.
- Build LLM-based pipelines for auto-documentation, PR reviews, dependency upgrades, and security scans.
Other
- 12+ years of progressive experience in software engineering, including 5+ years in a senior technology leadership role.
- Strong business acumen with ability to balance long-term innovation with near-term deliverables.
- Experience managing engineering budgets, vendor relationships, and capital allocation.
- Prior experience working with AI product development or developer platform teams.
- Master's degree in Computer Science, Engineering, or related discipline.
