Staff Technical Product Manager (Platform)
Zeitview is hiring a Staff Technical Product Manager to own the roadmap for its shared platform and core data model — representing large-scale geospatial, imagery, and inspection datasets as APIs, services, and governed platform primitives. It's a deeply technical PM role partnering with engineering, data, and product teams, hybrid in the SF Bay Area or Boston.
- Compensation
- $215K–$225K / yr
- Location
- Mountain View, California, United States
- Work setup
- Not specified
- Seniority
- Staff
- Employment
- Not specified
- Experience
- 5+ years
- Category
- Product
- Posted
Skills
Must have
- Candidates must currently live in the Boston or San Francisco Bay area
- 8+ years of professional experience, including 5+ years in product management
- Meaningful experience owning technical platform, data, infrastructure, developer, or AI-enabling products
- Built and shipped enterprise B2B SaaS products or platforms used by multiple teams or product surfaces
- Fluency with data modeling, schemas, APIs, event systems, distributed systems, data pipelines, warehouses, or analytics infrastructure
- Able to hold their own in architecture and technical design discussions with senior engineers and data practitioners
- Has made consequential build-vs-buy, abstraction, architecture, reliability, or scalability trade-offs
- Translate complex technical capabilities into clear product requirements and platform interfaces
- Delivered ambiguous, cross-functional programs where alignment and influence mattered more than authority
- Fluent in quantitative reasoning; can define metrics showing whether platform investment creates value
- Understands enterprise expectations around security, permissions, privacy, governance, compliance, and reliability
Nice to have
- 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 with operational systems where digital workflows connect to physical-world activity
Full description
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Location: Mountain View,California,United States
***We are only open to candidates who are currently living in either Boston or the San Francisco Bay area.*About Us**:
Zeitview is the leading intelligent aerial imaging company for high-value infrastructure, providing businesses with actionable, real-time insights to recover revenue, reduce risk and improve build quality. We serve customers in the solar, wind, insurance, construction, real estate, and critical infrastructure industries. Trusted by the largest enterprises in the world, Zeitview is active in over 70 countries. Our mission is to accelerate the global transition to renewable energy and sustainable infrastructure through advanced inspection solutions. Take a look at our latest achievements here!
This role in one paragraph:
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.
Responsibilities:
- 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.