Staff Technical Product Manager, Zeitview

• 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

Desirable

• 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