GPM – IoT & Asset Intelligence

The Role

As Group Product Manager - IoT & Asset Intelligence, you will own the product portfolio responsible for

monitoring, interpreting, and acting on signals from company’s installed asset base - solar plants,

inverters, batteries, and hybrid energy systems. This is a senior, hands-on role with direct accountability

for outcomes across a domain where software decisions have immediate physical consequences: a

missed alert means a degraded plant; a poorly routed signal means a preventable liability.

The core of this role is the intelligence layer - turning raw hardware signals into high-confidence,

actionable information that the right stakeholder can act on without needing to interpret the data

themselves. Product decisions here directly affect plant uptime, field-force utilisation, financial liabilities,

and customer trust.

Scope & Ownership

● Own the asset monitoring and intelligence product portfolio - including plant health monitoring,

alert detection and triage logic, remote corrective action workflows, and customer-facing

performance visibility. Scope spans solar plants today and extends to batteries and hybrid energy

systems as company’s product portfolio expands.

● Build the intelligence layer that turns raw IoT signals into confident, stakeholder-ready

information - defining what constitutes a meaningful alert, how severity is assessed, which

issues can be resolved remotely versus require a field dispatch, and how false positive rates are

reduced over time.

● Unify data streams from heterogeneous hardware (inverters, meters, battery management

systems, hybrid controllers) into a coherent data model that powers downstream products

reliably - without requiring every consumer of that data to understand the underlying hardware

complexity.

● Extend monitoring and intelligence capabilities to batteries and hybrid systems - understand how

the data model, alert logic, and health metrics differ from solar-only plants, and build a product

layer that handles multi-asset homes without fragmenting the platform.

● Design the information surfaces that enable each stakeholder to act with confidence - a central

response team that needs system-level triage context, field teams that need precise dispatch

briefs, and customers who need clear, jargon-free visibility into their plant and energy system

health.

● Own the signal-to-dispatch handoff - define what a well-formed, actionable dispatch looks like so

that field scheduling and execution teams can act on it without re-investigating the problem.

Quality of this output is a core accountability of the role.

● Identify and address structural noise in the alert pipeline - recurring false positives, signals that

don’t close the loop after resolution, and patterns that indicate a model or data quality problem

rather than a real asset issue.

● Set priorities across product areas and coach PMs on problem framing, solution quality, and

decision-making under data uncertainty.

● Partner with engineering to balance near-term reliability work with the foundational data

architecture investments required to scale the intelligence layer across asset types.

What Success Requires

● 8–10+ years of product management experience, with meaningful depth in IoT, telemetry, asset monitoring, or intelligence systems - energy management, fleet telematics, smart infrastructure, predictive maintenance, or similar contexts where physical signals drive operational decisions.

● Experience building products on top of IoT or sensor data - understands data quality challenges (signal inconsistency, false positives, dropout, protocol variance), can reason about alert logic from first principles, and knows how to build feedback loops that improve signal fidelity over time.

● Familiarity with multi-asset or multi-hardware environments is a meaningful advantage - experience spanning solar inverters, battery systems, or hybrid energy controllers is directly relevant. Candidates who have worked on EV charging infrastructure, home energy management systems, or storage-integrated solar platforms are particularly well-suited.

● Comfort making decisions with imperfect data - can reason through asymmetry, missing signals, and competing interpretations without waiting for perfect information, while being explicit about where uncertainty lives and how it should affect downstream action.

● Technical fluency sufficient to engage credibly with engineers on data models, MQTT pipelines, API design, and system architecture. Act as a genuine peer to Engg, helping identify the right questions and pressure-test design choices.

● Proven experience owning business outcomes in signal-driven or asset-monitoring environments (alert precision, false positive rates, time-to-detection, liability reduction, plant uptime).

● Demonstrated capability to lead and coach PMs - sets a high bar on problem framing and solution quality, and builds an environment where the team owns problems rather than waiting for direction.

● Active use of AI tools in day-to-day product work - can point to specific, concrete ways AI has changed how they work, and is curious about how AI changes alert intelligence, anomaly detection, and predictive maintenance in an IoT product context.

● Excellent cross-functional credibility with engineering and operations leaders - built through judgment and follow-through.