Director, Engineering – Title Automation

🕒 vor 20 Tagen

🏄 California – Remote

🏄 California – Remote

💵 $197.200 - $263.000 / Jahr

⏰ Vollzeit

🔴 Experte

🖥 Softwareentwickler

🦅 H1B-Visum-Sponsor

Dieses Unternehmen hat in der Vergangenheit H1B-Visa gesponsert.

👻 Geisterscore 0%

Was es bedeutet: wie wahrscheinlich diese Stelle offen bleibt, ohne dass aktiv eingestellt wird.So liest du es: 60 % oder höher heißt, wir halten das für einen Geisterjob. Niedrigere Werte sind weniger bedenklich.Wie wir werten: Dauer offen, Neuveröffentlichungen, offene Stellen vs Teamgröße, wie schnell Stellen geschlossen werden, und ob ein Gehalt angegeben ist.Hinweis: eine Schätzung aus öffentlichen Daten, kein Urteil über das Unternehmen. Echte Stellen können hoch punkten, nutze es also als Hinweis, nicht als Fakt.

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First American

WebsiteLinkedInAlle Stellen

10.000+ Mitarbeiter

Gegründet 1889

🏠 Immobilien

💸 Finanzen

🏢 Unternehmen

Real Estate • Finance • Enterprise

First American ist ein traditionsreiches Unternehmen, das seit 1889 tätig ist und sich zu einer Organisation mit 9 Milliarden Dollar Umsatz, über 20. 000 Mitarbeitern und mehr als 700 Büros weltweit entwickelt hat. Das Unternehmen bietet eine Reihe von Produkten und Dienstleistungen an, die Hauskäufer, Verkäufer, Unternehmen und Investoren im Immobilienmarkt unterstützen. Mit einem starken Fokus auf Mitarbeiterengagement und Unternehmenskultur legt First American Wert auf Innovation, Technologie und gesellschaftliches Engagement, um die Transformation innerhalb der Immobilienbranche voranzutreiben.

Beschreibung

• 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

🎯 Anforderungen

• 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

🏖️ Vorteile

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