Director, Engineering - Title Automation

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 headings

for section headings like About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. But we should map content to these headings appropriately. The instruction: "use

for section headings (e.g. About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule)." So we should use those exact headings? It says e.g., meaning examples. Probably we should use those headings where appropriate. We need to include a section only when posting has real, specific content for it. So we need sections like About the role (maybe corresponds to "Who We Are" and "What We Do"?), Responsibilities (What You'll Do), Requirements/Qualifications/Skills (What You'll Bring and Ideally...), Benefits (What We Offer), Pay (Pay Range). Schedule not present, so omit. Also we should not repeat job title as heading. No Job ID etc. Remove boilerplate like EEO etc. Also remove navigation etc. We need to preserve all substantive information. Thus produce something like:

About the role

... content from Who We Are and What We Do ...

Responsibilities

• ... each bullet from What You'll Do ...

Requirements

• ... from What You'll Bring ...

Maybe also Skills section? Could combine Requirements and Skills. But we can have Qualifications separate? The instruction: prefer a few substantive sections over many thin ones. So maybe combine Requirements and Qualifications into one? But we have headings list: About the role, Responsibilities, Requirements, Qualifications, Skills, Benefits, Pay, Schedule. We could use Requirements for core qualifications, Skills for technical skills, Qualifications for experience? Might be overkill. Better to use: About the role, Responsibilities, Requirements (covers What You'll Bring and Ideally...), Benefits, Pay. That's 5 sections. That's fine. We must not include placeholder text. Ensure we include all substantive info. Let's extract content. Who We Are: paragraph about First American, people first, accolades, etc. Also "For more information, please visit www.careers.firstam.com." That's maybe minor metadata but we can keep as part of About the role. What We Do: description of Remote Work, transformative engineering org, Director of Engineering role, etc. That's also about role. Thus About the role section can combine Who We Are and What We Do. Responsibilities: list from "What You'll Do". Need to break into bullet points. Let's parse What You'll Do paragraphs: - 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 many bullet points. We'll output as

• each. Requirements: from "What You'll Bring" and "Ideally, You'll Also Have Experience With". We'll combine. What You'll Bring bullets: - 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: - 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. We'll combine into Requirements section (maybe also Skills). But we can keep as Requirements. Benefits: from "What We Offer". Paragraph: "By choice, we don’t simply accept individuality – we embrace it, we support it, and we thrive on it! Our People First culture is inclusive for all employees - not just because it's the right thing to do, but because it's the key to our success. We are proud to foster an authentic and inclusive workplace For All. You are free and encouraged to bring your entire, unique self to work. First American is an equal opportunity employer in every sense of the term. 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." We need to strip EEO boilerplate? The instruction: Remove cookie/navigation/legal/EEO/equal-opportunity/scam-warning boilerplate, duplicated lines, and application instructions. So we should remove the equal opportunity employer line. Also maybe the "First American is an equal opportunity employer in every sense of the term." That's EEO boilerplate, remove. Also maybe the "Based on eligibility, First American offers a comprehensive benefits package ..." keep. Thus Benefits section:

  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.

  plus maybe the preceding sentences about People First culture? Those are not boilerplate; they are substantive about culture. We can keep them. Thus Benefits section could include the People First culture paragraph plus benefits. Pay: from "Pay Range: $197,200.00 - $263,000.00 Annually 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. Note that the following statements only apply to candidates who will be working from an unincorporated area within Los Angeles County." Then there is a bunch of legal stuff about Fair Chance Ordinance etc. That's legal boilerplate; we should remove that. Also the note about Los Angeles County maybe minor metadata but could be kept? It's not boilerplate but it's a note about location-specific statements. Might be considered minor metadata; we could fold into a short

  or drop. The instruction: "Do NOT put Job ID / requisition numbers as headings — fold minor metadata into a short

  or drop it." So we could include a short

  about the note. But the note includes legal statements about Fair Chance Ordinance etc. That's legal boilerplate; we should remove. The note says: "Note that the following statements only apply to candidates who will be working from an unincorporated area within Los Angeles County." Then the following statements are about Fair Chance Ordinance etc. Those are legal boilerplate; remove. So we can drop that entire note