Director, Engineering - Title Automation - Remote

We need to output HTML fragment with sections: About the role? Actually the posting includes "Who We Are", "What We Do", "What You'll Do", "What You'll Bring", "Ideally, You'll Also Have Experience With", "Pay Range", "What We Offer". We need to use

for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. But we must only include sections when posting has real specific content. We need to map content to these headings. We have: - About the role: maybe "Who We Are" and "What We Do" combined? Could be "About the role". We'll include a section with heading

About the role

and include paragraphs summarizing who they are and what they do (but we must not invent or summarize away detail; we must preserve all substantive information. However we can combine paragraphs but must keep details. We can include multiple

inside section. - Responsibilities: corresponds to "What You'll Do". We'll list bullet points for each duty. Use

• . - Requirements/Qualifications/Skills: "What You'll Bring" and "Ideally, You'll Also Have Experience With". Could be Requirements (mandatory) and Qualifications (preferred). We'll create sections: Requirements (mandatory) and Preferred Qualifications (or Skills). But headings allowed: Requirements, Qualifications, Skills. We need to decide. We have Pay Range: we have a Pay section. We have Benefits: "What We Offer" includes benefits description. Schedule: not mentioned, so we should not include Schedule. We must not include boilerplate like EEO etc. Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The posting includes some EEO statements near the end: "First American is an equal opportunity employer..." and also the Fair Chance statements. Those are boilerplate; we should remove them. Also the note about Los Angeles County etc. That's likely boilerplate; we should remove. We must preserve all substantive information. So we need to keep the Pay Range statement, the benefits description, the responsibilities, the requirements, etc. We must not repeat the job title as heading. Not include Job ID. We must output only HTML fragment. Let's extract substantive content: Who We Are: paragraph about First American, people-first culture, accolades, etc. What We Do: paragraph about Remote Work, transformative engineering organization, Director of Engineering role, leading distributed engineering org, etc. What You'll Do: many bullet-like paragraphs. We need to turn them into list items. Let's parse "What You'll Do" section: - Own the Data and Document Intelligence Platform - Define and evolve the architecture for a production-grade document intelligence system that extracts, structures, and governs data from title insurance documents at scale — turning unstructured document images into versioned, reusable, ML-ready data assets. - Own the platform that emits title production events to the data lake, decoupling operational systems from analytics and enabling downstream modeling and data science consumption. - Lead the development and maintenance of the canonical data model for title production — a unified ground truth that spans both manual and automated order workflows and serves as the foundation for ML training, evaluation, and automation. - Drive document classification programs, including expanding scope across new document types and geographies. - Partner with data science and AI governance teams to maintain labeled training datasets, accuracy benchmarks, and evaluation standards that underpin model trustworthiness. - Scale AI-Powered Title Automation - Own the engineering programs that expand First American's AI-driven title production platform — Sequoia — across new order types, geographies, and title production scenarios. - Lead automated generation of title search packages and related outputs built on top of the structured data platform, moving proof-of-concept programs into production. - Define sequencing, investment tradeoffs, and measurable outcomes for automation programs that directly grow Sequoia's coverage and accuracy. - Set Technical Direction and AI-Ready Architecture - Define architecture and engineering standards across document processing, event-driven data pipelines, data modeling, ML lifecycle, and the enterprise AI platform (Databricks, Unity Catalog, MLflow, or equivalents). - Build a governed, AI-ready data foundation — metadata and lineage, data contracts, lifecycle controls, strong data quality, and open interfaces — that makes automation built on top of it trustworthy. - Set the domain's approach to responsible AI engineering: model evaluation frameworks, ground truth governance, production deployment standards, drift detection, and human accountability. - Drive technical build/buy/modernize decisions, balancing interoperability, time to value, and sound economics. - Operate as a Product Owner and Cross-Functional Partner - Partner with Product on customer needs, desired outcomes, adoption, and experience; own the engineering approach to service boundaries, self-service capabilities, and technical delivery. - Partner with Product on investment tradeoffs, balancing platform modernization, technical debt, delivery, and responsible experimentation. - Collaborate with Title Operations, Data Science, and peer engineering leaders to ensure the data and automation capabilities you build are aligned to production outcomes and operational realities. - Build High-Performing, Distributed Engineering Teams - Build an inclusive, psychologically safe environment where engineers can grow, challenge ideas constructively, and deliver exceptional results. - Lead through engineering managers; develop them into leaders who can own their programs without you in the room. - Own organizational health and talent outcomes including hiring, performance, career development, and succession; raise the talent bar consistently. - Drive Delivery and Modernization Excellence - Own the domain roadmap and the investment tradeoffs that shape it; apply ROI discipline and redirect when return lags. - Lead modernization of production data and document platforms while protecting downstream consumers and maintaining business continuity. - Own engineering capacity planning and transparent intake, making commitments, dependencies, and delivery risks visible while protecting team focus. - Establish Operational Excellence and Cost Discipline - Own operational standards across observability, service levels, incident response, on-call, resilience, disaster recovery, release controls, and platform support. - With Security, Privacy, and Governance partners, enforce production-readiness guardrails for access control, lineage, auditability, governance, and data quality. - Drive cost and performance discipline through metrics, postmortems, and automation that strengthen reliability, efficiency, and customer trust. That's a lot; we can keep as list items. What You'll Bring: list of requirements. Paragraph: - Experience owning the strategy, architecture, and operational outcomes of a large-scale production data or AI platform serving many teams, workloads, and users. - Deep technical fluency in distributed data processing, data lakes and lakehouses, cloud data warehouses, event-driven architectures, ingestion, orchestration, and production pipelines. - Experience with document intelligence, unstructured data extraction, or ML-based data processing at production scale. - Technical fluency in AI/ML lifecycle management — model evaluation, ground truth governance, production deployment, versioning, and drift detection. - Strong understanding of cloud networking, identity and access, storage, compute, resilience, and cloud-native services. - Technical fluency in Infrastructure as Code and CI/CD, with experience guiding automated provisioning and delivery including quality and governance controls. - Experience modernizing complex data environments and migrating business-critical workloads without disrupting consumers. - Strong architectural and vendor judgment, including evidence-based build/buy tradeoffs across durability, time to value, interoperability, operability, and cost. - Experience shaping operating models and leading distributed teams through technical and people leaders in a matrixed organization. - A record of setting technical strategy, guiding investment decisions, and delivering measurable business outcomes in partnership with Product and business leaders. - Practical expertise in operational excellence, governance, security, data quality, cost management, and performance at scale. - Excellent executive communication and change leadership, with the ability to build alignment and explain the business consequences of technical choices. - Inclusive leadership and a record of developing engineering managers, building a leadership bench, and creating accountability for sustained outcomes. Ideally, You'll Also Have Experience With: list. - Experience With Modern lakehouse and cloud data warehouse platforms such as Databricks, Snowflake, or equivalents, including Unity Catalog, MLflow, or comparable data and ML governance tooling. - Event-driven architectures and data pipeline design for operational and analytical workloads. - Document intelligence, OCR, extraction models, schema design, versioning strategies, and accuracy measurement. - Open table formats, data catalogs, lineage, semantic modeling, data contracts, and lifecycle management. - Designing or operating AI platforms that support data science, machine learning, data products, and AI-enabled experiences. - Highly regulated industries such as financial services, insurance, or real estate. Pay Range: "$197,200.00 - $263,000.00 Annually" plus explanation. What We Offer: paragraph about People First culture, benefits: medical, dental, vision, 401k, PTO/paid sick leave, employee stock purchase plan. We should not include EEO statements. Now we need to map to headings. We could have:

  About the role

  with paragraphs combining Who We Are and What We Do.

  Responsibilities

  with
  • items from What You'll Do.

    Requirements

    with
    • items from What You'll Bring.

      Preferred Qualifications

      maybe using

      Qualifications

      for the Ideally section.

      Benefits

      with paragraph from What We Offer.

      Pay

      with paragraph about Pay Range. We should not include Schedule. We must ensure we don't create sections with filler like "commensurate with experience". Not present. Now produce HTML. We need to preserve all substantive information; we must not lose any detail. So we need to include all the bullet points exactly as in the posting (maybe rephrase slightly but must not invent or summarize away detail). We can keep them as list items; we can keep the sentences as they are. We need to be careful not to include the boilerplate like "Based on eligibility, First American offers a comprehensive benefits package including medical, dental, vision, 401k, PTO/paid sick leave and other great benefits like an employee stock purchase plan." That's fine. We also need to include the Pay Range explanation: "This hiring range is a reasonable estimate of the base pay range for this position at the time of posting. Pay is based on a number of factors which may include job-related knowledge, skills, experience, business requirements and geographic location." That's substantive; we should keep it. We also need to keep the note about Los Angeles County? That seems like a legal condition; might be considered boilerplate? It's specific to location; but it's part of the posting. The instruction says remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. The Los Angeles County note is legal; might be considered boilerplate. However it's specific to candidates working from an unincorporated area within Los Angeles County. It's a legal statement; maybe we should remove it as it's legal boilerplate. The instruction says remove legal boilerplate. So we should remove that note and the Fair Chance statements. Thus we will not include those. Now produce HTML. Let's craft:

      About the role

      Join a team that puts its People First! 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 eleven 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