Job Title: Senior Product Manager - Asset Health

At BusPatrol, we’re on a mission to make school transportation safer for children and communities. As a leader in AI-powered safety solutions, we bring cutting-edge technology—AI, machine learning, and IoT—to school buses across North America. We’re the most trusted stop-arm safety program globally, delivering transparency and safety at scale. In short, this is purpose driven work that measurably changes behavior in the communities we serve.

Key Outcomes

This role is critical to transforming how we think about the health and lifecycle of our units deployed in the field and the experience of numerous internal and external stakeholders (target users). High-level goals for this new capability include:

Reduce mean time to resolve (MTTR) for bus and hardware issues by 25–50% within 12 months.

Increase in-field uptime of critical hardware kits (e.g., cameras, sensors, edge devices) by a defined target (e.g., X%) through improved monitoring, diagnostics, and maintenance workflows.

Clarify and prioritize asset criticality, enabling operations teams to focus on buses and routes with the greatest safety and enforcement impact.

Improve detection, triage and automated remediation of asset issues (e.g., false alarms, connectivity problems, firmware regressions) through better dashboards, alerts, and root-cause analysis tools.

Strengthen collaboration between Product, Hardware, Firmware, Data, Operations, and Support, with a shared set of metrics and a transparent roadmap in Jira.

Responsibilities

Own the Vision & Roadmap

Define the strategy for Asset Health across BusPatrol’s hardware portfolio, with a clear, data- driven strategy for reliability, availability, and lifecycle management.

Balance user empathy with enforcement rigor to drive behavior change.

Make clear trade-offs between short-term reliability fixes and longer-term platform investments, ensuring we build for scale.

Lead with Data and Insight

Define and own key performance indicators for Asset Health (e.g., MTTR, failure rates, uptime, alert precision/recall).

Leverage strong analytical skills to do impact sizing, opportunity assessment, and “Fermi style” estimation to guide decision-making.

Establish feedback loops with internal users and customers to continuously refine problem definitions, success metrics, and solutions.

Design for Predictive Maintenance & Operational Excellence

Partner with Hardware, Firmware, and Data teams to design telemetry and diagnostics needed to predict failures before they affect service.

Define health indicators and thresholds (e.g., error rates, connectivity drops, temperature, performance degradation) and ensure they are surfaced in usable tools.

Build or enhance internal tools, dashboards, and workflows that help Support and Operations quickly identify, triage, and resolve asset issues.

Incorporate behavioral design principles so internal users know when to act, what to do, and how to prioritize among competing alerts.

Drive Experimentation in a Regulated, B2G Environment

Innovate testing to design pilots, phased rollouts, and proxy metrics that work in a B2G context.

Collaborate with government partners and school districts to validate changes within legal and contractual frameworks.

Use structured experimentation and strong metrics to de-risk changes that affect enforcement, evidence quality, and service levels.

Foster Cross-Functional Alignment

Act as a quarterback for a broader set of teams when issues are root caused to various layers in the technology stack, hardware, firmware, software, human process

Partner closely with many stakeholder groups across the company

Communicate roadmap and trade-offs clearly to executives and external partners.

Champion Governance, Safety & Compliance

Ensure asset-related data and monitoring solutions respect privacy, retention, and evidentiary requirements, in collaboration with Legal and Compliance. Especially navigating these challenges from outside the United States.

Balance the need for rich telemetry and model training data with evolving data privacy and retention constraints.