Vice President, Engineering

Who We Are

Join a team that puts its People First! As a member of First American’s family of companies, Data & Analytics is a national provider of property-centric information, analytics, risk management and valuation solutions. First American maintains and curates the industry’s largest property and ownership dataset with over 7 billion document images. Our major platforms and products include: DataTree®, FraudGuard®, RegsData™, TaxSource™ and ACI®. The First American Data & Analytics division boasts more than 20 patents and remains at the forefront of innovation - leveraging technology and data to deliver best-in-class decisioning solutions. Fueled by our industry-leading data and using our technology and proprietary process, our solutions provide lenders, real estate and title companies with actionable insights - enabling them to make better, increasingly automated, decisions. With offices in all major metropolitan areas, including California and New York, DNA teams work collaboratively from across the country. Since 1889, First American (NYSE: FAF) has held an unwavering belief in its people. They are passionate about what they do, and we are equally passionate about fostering an environment where all feel welcome, supported, and empowered to be innovative and reach their full potential. Our inclusive, people-first culture has earned our company numerous accolades, including being named to the Fortune 100 Best Companies to Work For® list for ten consecutive years. We have also earned awards as a best place to work for women, diversity and LGBTQ+ employees, and have been included on more than 50 regional best places to work lists. First American will always strive to be a great place to work, for all. For more information, please visit www.careers.firstam.com.

What We Do

The Vice President of Engineering for DNA is a senior technology leader responsible for building and scaling data platforms, application ecosystems, and AI-enabled products that power next-generation analytical and transactional capabilities. This role sits at the intersection of data, application engineering, and AI, ensuring tight alignment between data foundations, services, and user-facing applications. You will lead global engineering teams delivering end-to-end products—from data ingestion and processing to APIs, intelligent services, and customer-facing applications. You will define architecture, scale global teams, and deliver high-quality products with predictable execution—while evolving the platform to be AI-ready by design, enabling machine learning and generative AI capabilities to be embedded across core workflows.

• Role is Hybrid out of Santa Ana, CA*

Key Responsibilities

Technical Strategy & Architecture

• Define and drive end-to-end architecture across data platforms, application services, APIs, and user-facing systems
• Design scalable systems supporting both analytical and transactional workloads
• Establish domain-driven design, service boundaries, and API-first architecture
• Architect AI-ready data foundations, including feature availability, metadata, and structures optimized for machine learning and AI use cases
• Define patterns for integrating AI/ML and generative AI capabilities into applications
• Lead modernization initiatives (cloud-native, microservices, platform consolidation)
• Establish standards for data governance, system design, resilience, and observability

Product & Platform Engineering

• Own delivery of end-to-end products, including:
• Analytical and data-driven applications
• Customer-facing and internal applications
• APIs, domain services, and shared platforms
• Partner with product leadership to translate strategy into scalable engineering roadmaps
• Lead development of AI-enabled features and intelligent applications
• Ensure strong SDLC practices (testing, CI/CD, release engineering)
• Drive engineering accountability for product performance, reliability, and user experience

Global Engineering Delivery

• Lead global engineering teams across multiple regions and time zones
• Establish product-aligned team structures with clear ownership of services and domains
• Implement delivery governance with clear milestones and measurable outcomes
• Optimize global delivery models to balance speed, quality, and cost
• Manage capacity planning, workforce strategy, and vendor partnerships

Operational Excellence & Reliability

• Own performance, uptime, scalability, and cost efficiency across platforms and applications
• Implement metrics-driven engineering management (velocity, quality, reliability, cost)
• Establish observability across data, services, and AI systems
• Drive SRE practices, including incident management and continuous improvement
• Implement MLOps/LLMOps practices, including model monitoring, performance evaluation, and lifecycle management
• Ensure compliance with security, privacy, and regulatory standards

Talent & Culture

• Build and scale global teams across:
• Application en