Pennymac - SVP, Engineering

Fabric•Los Angeles, CA

13h

About The Position

We are looking for a forward-thinking Senior Vice President (SVP) of Application Development to lead and scale our engineering organization in the next phase of our company’s growth. As a key member of the leadership team, you will be responsible for defining and executing a cohesive technology strategy across all product lines within our mortgage-focused fintech platform. You’ll bring deep engineering expertise in Python, TypeScript, and AWS, while also championing adoption of AI-enhanced engineering workflows using AI tools. This role requires not only technical and architectural vision, but also hands-on leadership, a strong grasp of the mortgage and lending ecosystem, and an ability to bridge business strategy with engineering execution.

Requirements

Master's degree in Computer Science, Engineering, or related discipline.
12+ years of progressive experience in software engineering, including 5+ years in a senior technology leadership role.
Expertise in: o js, Python, and TypeScript o Modern frontend frameworks (e.g., React, Next.js) o AWS cloud architecture (Lambda, API Gateway, DynamoDB, RDS, etc.) o 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.
Familiarity with eMortgage stack, MISMO standards, and secondary market data formats.
Proven success in building, leading, and scaling engineering teams at a high-growth technology company.
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.

Nice To Haves

AWS Solutions Architect or Mortgage Banking certifications (e.g., Certified Mortgage) highly preferred.

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.
Promote a culture of innovation, velocity, and excellence in software delivery.
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.
Integrate and govern the use of AI developer tools like Cursor, Devin, and Gitlab Copilot.
Build LLM-based pipelines for auto-documentation, PR reviews, dependency upgrades, and security scans.
Champion the use of AI for quality assurance, regression testing, and automated remediation.
Lead cloud architecture across AWS, including Lambda, ECS/EKS, API Gateway, S3, RDS, DynamoDB, Step Functions, and SQS.
Establish best-in-class DevSecOps practices including CI/CD pipelines, infrastructure-as-code (Terraform/CDK), observability (New Relic), and proactive alerting.
Oversee infrastructure resilience, disaster recovery, and multi-region high availability.
Lead engineering support for integrations with Encompass, ICE Mortgage Tech, MERS, UCD, Freddie Mac, Fannie Mae, MISMO, and Servicing systems.
Ensure that systems comply with regulatory and security frameworks including SOC2, ISO27001, CFPB, RESPA, and other lending-specific mandates.
Drive innovation in digital loan origination, pricing engines, eNote/eClose technologies, and credit decisioning.
Partner with Product, Risk, Legal, and Data teams to define technical feasibility and shape go-to-market timelines.
Translate complex business and compliance requirements into modular, API-first engineering solutions.
Attract, retain, and grow top-tier engineering talent with a strong focus on diversity, mentorship, and continuous learning.
Scale distributed teams across locations and time zones while maintaining alignment and culture.
Implement structured career ladders, performance reviews, and skills development programs.