Principal Product Manager, Vertical Solutions & AI

Hubble Network•San Francisco, CA

8h•Hybrid

About The Position

Hubble Network is building a global Bluetooth® network for machine-to-machine connectivity, differentiating itself as the first modem-less and gateway-less, direct-to-satellite network from off-the-shelf Bluetooth® Low Energy chips. The company is ideal for applications in logistics, AgTech, and maritime where economies of scale for volume consumer and enterprise asset tracking are a priority. Hubble aims to be the first billion-endpoint-connected network globally. As an early-stage, venture-backed startup, Hubble is supported by prominent investors and a founding team with a proven track record in venture funding, developing Amazon Sidewalk, launching space assets, and achieving successful exits. The company is seeking talented individuals to join their mission. This role is hybrid and can be based in San Francisco, CA or Seattle, WA.

Requirements

8+ years of product management experience in data and AI products, analytics, IoT, or B2B SaaS platforms.
Experience shipping data or AI/ML-powered capabilities that customers rely on in their daily operations.
Strong understanding of data quality, metadata, lineage, privacy, and access controls.
Experience working with legal and security teams on data privacy and governance.
Ability to engage credibly with data scientists, ML engineers, platform engineers, and business-development teams.
Strong commercial judgment around packaging and pricing.
Experience defining APIs, integrations, or enterprise data workflows.
Comfort operating in an ambiguous, early-stage market and validating demand directly with buyers.
Experience building vertical or industry-specific products on top of a horizontal platform, ideally in IoT, logistics, supply chain, or asset tracking.
Strong UX judgment, with a track record of shipping workflow-heavy B2B dashboards, alerting, and reporting for operations users.
Experience partnering with sales and GTM leaders on segment prioritization, market sizing, and launch planning.
All applicants must be U.S. citizens or lawful permanent residents (“green card holders”) as defined by ITAR (22 CFR §120.15).

Nice To Haves

A Sense of Urgency: Lead projects from concept to reality, rapidly and effectively.
First Principles Engineering: Have a strong understanding of the whys behind the what's; have the ability to extrapolate from first principles to complex system design.
High Learning Agility: Love to learn; have a grounded approach to recognizing your weaknesses and take the initiative to brush up on and sharpen your engineering foundations to better collaborate with your teammates with different backgrounds.
System-Level Design and Analysis: Understand the requirements flow down process and be able to quickly iterate on evolving requirements.
Excellent Communication Skills: Effectively convey ideas and communicate technical topics with engineering, build staff, and operations; run self-directed design reviews and participate in reviews of parallel systems.
Anticipation of Needs: Identify problems, think creatively, and rapidly produce reliable and cost-effective solutions to meet the ever growing and changing needs of an early-stage company.

Responsibilities

Own the strategy and roadmap for Hubble's data and AI-driven product capabilities.
Identify where data and AI can create differentiated value for customers, such as predictive alerts, anomaly detection, and operational insights.
Define requirements for data collection, normalization, metadata, quality, lineage, and documentation.
Establish product requirements for privacy, security, access controls, and data governance that protect customer trust.
Partner with Legal and Security on privacy and compliance.
Define how insights reach customers through dashboards, alerts, APIs, and integrations.
Develop packaging and pricing for data and AI-driven features.
Validate demand directly with customers and prospects.
Create metrics for data quality, feature adoption, retention, and revenue impact.
Partner with GTM to decide which verticals to pursue and in what order, based on pipeline, deal size, win/loss data, competitive position, technical fit, and reuse across verticals.
Define the capability set for each priority vertical, for example temperature excursion alerts and chain-of-custody reporting for cold chain; dwell time, cycle counts, and loss detection for pallet polling; utilization, geofencing, and theft alerts for tool monitoring.
Own the UX of verticalization, including vertical dashboards, alerting, onboarding, terminology, and reporting, and decide which elements are configured per vertical and which stay shared in the core platform.
Decide when a vertical need calls for a new capability, a configuration of existing ones, or a partner integration, so the platform does not split into one-off builds.
Turn field feedback, win/loss analysis, and customer requests into vertical requirements, packaging, and sales enablement.
Connect vertical solutions to the data and AI roadmap, such as predictive features and anomaly detection for each vertical.