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Staff Technical Product Manager

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Onsite

Staff Technical Product Manager

Zeitview

Staff Technical Product Manager

Skills

Data EngineeringProduct ManagementData ScienceData AnalysisMachine LearningAIProduct ManagerCompliance

1 month ago

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Important information


Salary:

$215,000 – $225,000 / year

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

25 September 2026

What they need


Who you are

  • 8+ years of professional experience, including 5+ years in product management
  • Meaningful experience owning technical platform, data, infrastructure, developer, or AI-enabling products
  • You have built and shipped enterprise B2B SaaS products or platforms used by multiple teams or product surfaces
  • Fluency with technical concepts including data modeling, schemas, APIs, event systems, distributed systems, data pipelines, warehouses, or analytics infrastructure
  • Hold your own in architecture and technical design discussions with senior engineers and data practitioners
  • You have made consequential build-vs-buy, abstraction, architecture, reliability, or scalability trade-offs
  • Translate complex technical capabilities into clear product requirements and platform interfaces that engineers can build from
  • You have delivered ambiguous, cross-functional programs where alignment and influence mattered more than organizational authority
  • Fluent in quantitative reasoning and can define metrics that demonstrate whether a platform investment is actually creating value
  • Understand enterprise expectations around security, permissions, privacy, governance, compliance, and reliability
  • Experience with geospatial data, imagery, remote sensing, computer vision, or asset inspection platforms
  • Experience with high-volume or complex data processing systems
  • Experience defining domain models or shared data architectures across multiple products
  • Experience building platforms that support machine learning, generative AI, or agent-based systems
  • Experience with data lineage, observability, governance, or master-data concepts
  • Experience working with operational systems where digital workflows connect to physical-world activity

What the job involves

  • Build the platform that powers every Zeitview product
  • Own the core data model and shared platform services that enable data capture, processing, analysis, and delivery across Zeitview’s products and verticals
  • Define how domain objects and large-scale geospatial, imagery, inspection, and operational datasets are represented, connected, processed, governed, and exposed to applications, customers, and AI systems
  • This is a technical, high-leverage product role for someone who cares about building reliable, scalable, extensible systems
  • You’ll work closely with product engineering, data engineering, data science, security, and product teams to turn fragmented systems and data into durable platform primitives that teams can build on with confidence
  • Own the roadmap for shared platform services and data capabilities
  • Work across product teams to understand platform needs, unblock high-value use cases, and drive consistency without unnecessarily constraining product innovation
  • Maintain a clear understanding of the domain model, datasets, services, APIs, and platform dependencies
  • Prioritize and make trade-offs legible to engineering, product, and leadership
  • Partner with engineering to build reliable, scalable APIs, services, pipelines, and interfaces that turn complex underlying systems into simple platform capabilities
  • Define canonical entities, relationships, contracts, events, permissions, and semantics used across the data lifecycle
  • Improve how application teams discover, understand, and consume shared capabilities
  • Define standards for data quality, lineage, governance, discoverability, documentation, reliability, and developer experience
  • Identify where shared capabilities should be standardized at the platform layer versus owned within individual products or verticals
  • Evaluate how AI and agent-based systems should interact with Zeitview’s data and platform capabilities, including the primitives required to make those systems reliable and scalable
  • Define success metrics for platform investments and measure adoption, reliability, reuse, and business impact

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