Enterprise Architect

Overview

Pennymac (NYSE: PFSI) is a specialty financial services firm with a comprehensive mortgage platform and an integrated business focused on the production and servicing of U.S. mortgage loans and the management of investments related to the U.S. mortgage market.

At Pennymac, our people are the foundation of our success and at the heart of our dynamic work culture. Together, we work towards a unified goal of helping millions of Americans achieve aspirations of home ownership through the complete mortgage journey.

Pennymac is accelerating its digital transformation across the mortgage lifecycle — and we are seeking a forward-thinking Enterprise Architect who brings an AI-first mindset to reimagine how technology powers loan origination — driving smarter, faster, and more intuitive experiences for our customers and teams. This role blends core enterprise architecture expertise (scalability, security, reliability, and developer experience) with leadership in AI-driven modernization.

The Architect will drive the end-to-end technical vision, from designing robust cloud-native systems to embedding intelligent, AI-enhanced workflows that improve productivity, accuracy, and time-to-close.

You will serve as the bridge between technology strategy and execution, ensuring our architecture supports business growth, operational excellence, and innovation through automation and intelligence.

• Define and evolve the end-to-end architecture for Loan Originations platforms across customer, workflow, and data layers.
• Design cloud-native, event-driven systems leveraging AWS, Node.js, Type Script, Python, and React for scalability and resilience.
• Own architecture for non-functional requirements (NFRs) — including performance, availability, observability, and cost efficiency.
• Partner with engineering leadership to define technical roadmaps and modernization strategies.
• Architect and operationalize AI solutions across document processing, underwriting, credit decisioning, and loan workflow orchestration.
• Implement agentic AI systems using AWS Bedrock, Lang Chain, or similar frameworks for autonomous workflow execution.
• Embed AI copilots and code assistants to improve engineering velocity, quality, and defect prevention.
• Build retrieval-augmented generation (RAG) patterns for secure, explainable, and contextual LLM applications.
• Drive modernization from monolith to microservices and event-based architectures.
• Establish standards for API-first design, infrastructure-as-code (IaC), and serverless computing.
• Partner with Dev Ops teams to enhance observability, CI/CD automation, and cloud cost optimization.
• Champion Agile delivery excellence, ensuring architecture aligns with iterative development and incremental business value delivery.
• Enforce architecture governance ensuring all systems meet Pennymac’s standards for security, auditability, and compliance.
• Implement Responsible AI frameworks ensuring transparency, fairness, and explainability in automated decisions.
• Define model and data governance policies for AI and analytics systems in production.
• Partner with product, data, and business stakeholders to translate objectives into scalable technical designs.
• Mentor engineers and solution architects in modern architecture patterns and AI adoption.
• Contribute to Pennymac’s AI Center of Excellence, sharing best practices across the enterprise.

• Bachelor’s degree in Computer Science or related field, or equivalent work experience; MS a plus
• 15+ years of progressive experience in software architecture, engineering, or platform strategy roles.
• Strong hands-on expertise in:
• Programming: Python, Type Script, Node.js, React
• Cloud: AWS (Lambda, ECS, S3, Dynamo
  
  DB, Step Functions, Bedrock, Sage Maker)
• Architecture: Event-driven systems, microservices, APIs, and distributed design
• Proven experience defining NFRs — performance, scalability, reliability, and cost optimization.
• Experience in AI and GenAI system design
  , including LLM integration, RAG, and MLOps.
• Working knowledge of agentic AI frameworks (Lang Chain, Bedrock Agents, AutoGPT, etc.).
• Deep familiarity with Agile delivery
  , including backlog-driven…