Director, Engineering – Title Automation

🔥 12 hours ago

🏄 California – Remote

🏄 California – Remote

💵 $197.2k - $263k / year

⏰ Full Time

🔴 Lead

🖥 Software Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 0%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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First American

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1889

🏠 Real Estate

💸 Finance

🏢 Enterprise

Real Estate • Finance • Enterprise

First American is a historical company that has been operating since 1889, evolving into a $9 billion organization with over 20,000 employees and more than 700 offices worldwide. The company provides a range of products and services that assist homebuyers, sellers, businesses, and investors in the real estate market. With a strong focus on employee engagement and culture, First American emphasizes innovation, technology, and community involvement, driving transformation within the real estate industry.

📋 Description

• Own the Data and Document Intelligence Platform architecture and operations • Define and evolve a production-grade document intelligence system that extracts, structures, and governs title insurance document data at scale • Own the platform emitting title production events to the data lake • Lead development and maintenance of the canonical data model for title production • Drive document classification programs across new document types and geographies • Partner with data science and AI governance teams on labeled datasets, accuracy benchmarks, and evaluation standards • Own engineering programs expanding the Sequoia AI-driven title production platform across order types, geographies, and scenarios • Lead automated generation of title search packages and related outputs, moving proof-of-concept programs into production • Define sequencing, investment tradeoffs, and measurable outcomes for automation programs • Set architecture and engineering standards across document processing, event-driven data pipelines, data modeling, ML lifecycle, and enterprise AI platforms • Build a governed, AI-ready data foundation with metadata, lineage, data contracts, lifecycle controls, data quality, and open interfaces • Establish responsible AI engineering practices, including evaluation frameworks, ground truth governance, deployment standards, drift detection, and human accountability • Drive technical build/buy/modernize decisions • Partner with Product on customer needs, outcomes, adoption, service boundaries, self-service capabilities, and delivery • Collaborate with Title Operations, Data Science, and engineering leaders • Build inclusive, psychologically safe, distributed engineering teams • Lead through engineering managers and develop them into leaders • Own hiring, performance, career development, succession, and organizational health • Own the domain roadmap, investment tradeoffs, capacity planning, intake, commitments, dependencies, and delivery risks • Lead modernization while protecting downstream consumers and business continuity • Own operational standards for observability, service levels, incident response, on-call, resilience, disaster recovery, release controls, and platform support • Enforce production-readiness guardrails for access control, lineage, auditability, governance, and data quality • Drive cost and performance discipline through metrics, postmortems, and automation

🎯 Requirements

• 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, including 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 • Experience modernizing complex data environments and migrating business-critical workloads without disrupting consumers • Strong architectural and vendor judgment, including evidence-based build/buy tradeoffs • Experience shaping operating models and leading distributed teams through technical and people leaders in a matrixed organization • Record of setting technical strategy, guiding investment decisions, and delivering measurable business outcomes 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 • Inclusive leadership and a record of developing engineering managers and building a leadership bench • Ideally, experience with Databricks, Snowflake, Unity Catalog, MLflow, event-driven architectures, document intelligence, OCR, extraction models, schema design, open table formats, data catalogs, lineage, semantic modeling, data contracts, AI platforms, and regulated industries

🏖️ Benefits

• Medical insurance • Dental insurance • Vision insurance • 401k • PTO/paid sick leave • Employee stock purchase plan • Inclusive workplace and equal opportunity employment