Staff Technical Product Manager (Platform)

Zeitview; Boston (MA); On-site; USD 150,000 - 210,000; Full time

Job summary

You will help build platforms supporting ML/AI workflows, ensure data quality and lineage, and drive cross-team alignment while enabling product innovation. The role combines strategic leadership with hands-on architecture and delivery, reporting into the platform or data leadership track.

Qualifications

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

Responsibilities

• Build the platform powering Zeitview products.
• Own core data model and shared platform services for capture, processing, analysis, and delivery.
• Define representation of domain objects and large-scale geospatial, imagery, inspection, and operational datasets across platforms.
• This is a technical, high-leverage product role focused on reliable, scalable systems.
• Collaborate with product engineering, data engineering, data science, security, and product teams to turn fragmented systems into durable platform primitives.
• 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 constraining innovation.
• Maintain 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.
• Define canonical entities, relationships, contracts, events, permissions, and semantics 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 products/verticals.
• Evaluate how AI/agent-based systems should interact with Zeitview’s data and platform capabilities, including required primitives.
• Define success metrics for platform investments and measure adoption, reliability, reuse, and business impact.

Skills

Platform ownership

Architecture discussions

Security & governance

Data modeling & APIs

Distributed systems

Data pipelines

Geospatial data

AI platforms

Quantitative reasoning

B2B SaaS

Education

Experience in product management

Job description

Responsibilities

• 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

Qualifications

Meaningful experience owning technical platform, data, infrastructure, developer, or AI-enabling productsHold your own in architecture and technical design discussions with senior engineers and data practitionersYou have made consequential build-vs-buy, abstraction, architecture, reliability, or scalability trade-offsUnderstand enterprise expectations around security, permissions, privacy, governance, compliance, and reliabilityFluency with technical concepts including data modeling, schemas, APIs, event systems, distributed systems, data pipelines, warehouses, or analytics infrastructureYou have delivered ambiguous, cross-functional programs where alignment and influence mattered more than organizational authority8+ years of professional experience, including 5+ years in product managementTranslate complex technical capabilities into clear product requirements and platform interfaces that engineers can build fromYou have built and shipped enterprise B2B SaaS products or platforms used by multiple teams or product surfacesFluent in quantitative reasoning and can define metrics that demonstrate whether a platform investment is actually creating valueExperience working with operational systems where digital workflows connect to physical-world activityExperience with data lineage, observability, governance, or master-data conceptsExperience building platforms that support machine learning, generative AI, or agent-based systemsExperience defining domain models or shared data architectures across multiple productsExperience with high-volume or complex data processing systemsExperience with geospatial data, imagery, remote sensing, computer vision, or asset inspection platforms