IntelliSense.io is offering a great opportunity for a talented Product Manager to lead the development and delivery of Industrial AI agents for global Minerals and Metals operators. Today we are deploying AI-powered software solutions that drive real-time optimisation, delivering millions in value to some of the world’s largest industrial companies.
We are pioneers in Objective AI ( ODAI) with fundamental physics that characterises the physical world with out-of-the-box industry-specific solutions. AI delivers high-value decision recommendations, acting as the brains of the operation. These recommendations are delivered to humans as their role-specific co-pilots augment human intelligence or direct to the execution systems (machines), making operations autonomous.
With a global team of 70 employees and offices across four continents, our HQ is in Cambridge, UK, with regional offices in Saudi Arabia, Chile, Australia, and Ireland.
We are evolving our Industrial AI Operating System for the global mining sector from a suite of solutions into a unified platform. We're looking for a Product leader to own the foundational data architecture and cross-app consistency required for this transition. This role is ideal for an experienced professional who understands the critical impact of robust data strategy in industrial environments.
Data in/out governance You will define and own how data enters and leaves the platform. Today that is ad hoc. You will replace it with a principled, scalable strategy (covering integration standards, ingestion rules, and egress governance) and make it stick across engineering and customer deployments.
Cross-app feature strategy global optimisation configurations, Core Features (equations, alerts, and reports) that span every product and are the main tools of our agentic offering. Right now each app treats them differently. You will unify the strategy, resolve the inconsistencies, and produce specifications that engineering can build to consistently.
Edge deployment: Our Edge recommendation layer is a core part of the product and the goal is to have it running on every mine. You will own decisions around model drift, update cadence, and auto-pause safety.
Platform cost reduction: You will identify software patches and improvements that reduce the internal cost-to-mine, translating operational pain into a prioritised product roadmap.
Essential
5+ years in enterprise software product management, owning a complex, multi-component product end-to-end
Background in industrial, scientific, or process-industry software — mining, energy, manufacturing, chemicals, or similar
Strong grasp of data integration patterns: APIs, event-driven architectures, ETL, and the governance challenges they bring
Experience making cross-platform feature strategy decisions — what gets standardised, what gets customised, and why
Able to move between strategic thinking and precise, buildable specifications without losing altitude
Strong stakeholder management across engineering, sales, and customer success
Experience working in highly automated, modern product operations environments
Nice to have
Experience with edge computing or on-premise deployment in industrial environments
Familiarity with ML model lifecycle management — drift detection, retraining, and what that means for end users
Exposure to industrial data standards or ontologies (ISO 15926, OSDU, or similar)
Experience working with mining, metallurgical, or geological domain experts
A documented data strategy and governance framework in place and adopted by engineering
Cross-app feature inconsistencies resolved and shipped as a unified standard
Edge model drift policy defined, auto-pause safety specified, and customer communication framework live
Measurable reduction in cost-to-mine from platform improvements
Existing deployment base brought to a consistent, standardised state
You have spent your career making complex industrial or scientific software work for demanding customers. You understand that in this industry, a poorly governed data integration or an unexpected auto-pause event has real operational consequences, not just a ticket in the backlog. That understanding shapes how you write requirements, how you manage risk, and how you earn trust.
You are a systems thinker who can hold the end-to-end value chain in your head while staying precise about the detail that matters. You do not need a perfect brief to get started.
Excited to shape the future of Industrial AI?
We’d love to hear from you!
