We are seeking an experienced Senior Product Manager to own the vision, strategy and execution of the roadmap for SmartSense CRE, Ecolibrium's commercial real estate product line within the broader SmartSense platform. The role will work closely with Engineering, Design, Field Operations, Sales and Delivery to turn market insight and customer feedback into products that are competitive, high-quality and aligned to Ecolibrium's business goals.
The Senior Product Manager will lead market research, define product strategy, guide development from concept to launch and track performance against clear KPIs. SmartSense is a technically layered product spanning real-time IoT telemetry, deterministic rules engines, machine learning models and, in select modules, conversational AI. This role requires strong strategic thinking, genuine technical fluency across these layers, stakeholder management and the ability to inspire and align teams around a shared product vision. Requires 7+ years of relevant experience.
Key Responsibilities
Develop and implement product vision, strategy and roadmap for SmartSense CRE, in alignment with Ecolibrium's business goals.
Conduct thorough market research and competitive analysis, including in AI-enabled energy and building management tooling, to identify trends, opportunities and customer needs.
Collaborate with Engineering, Design and other teams to guide product development from concept through to launch, ensuring timely and high-quality delivery.
Define product requirements for AI-driven features (ML forecasting models, conversational AI modules) with the same rigour as deterministic features, including clear scoping of what the AI is and is not responsible for.
Engage internal and external stakeholders, including customers, to gather feedback, understand requirements and ensure product success.
Define and monitor key product performance indicators (KPIs) to measure success and inform product decisions.
Drive continuous product improvement through customer feedback, data analysis and industry best practices.
Foster a collaborative environment and work closely with cross-functional teams to achieve product goals.
Translate market insights and customer needs into actionable product requirements and prioritised backlogs.
Partner with Sales and Presales to support go-to-market activities, positioning and customer-facing product narratives, ensuring AI capabilities are represented accurately and never overstated.
Lead and motivate cross-functional teams, setting a compelling product vision that inspires others to deliver against it.
Qualifications & Experience
Essential
Bachelor's degree in Business, Engineering, Computer Science or a related field; an advanced degree is a plus.
7+ years of experience in product management, with a proven track record of leading successful product initiatives.
Experience in IoT, building management systems or related industries is highly desirable.
Strong understanding of product development processes, market research techniques and data analysis tools.
Working fluency with AI product concepts: able to distinguish deterministic rule-based logic from machine learning and from LLM-based conversational features, and to make sound product decisions about where each is appropriate.
Proven ability to lead and motivate cross-functional teams without direct authority.
Ability to think strategically and translate market insights into actionable product strategies.
Excellent verbal and written communication skills, with the ability to communicate complex technical and AI-related concepts to diverse, including non-technical, stakeholders.
Strong customer orientation with a passion for creating products that deliver exceptional value and user experience.
Desirable
Experience as a visionary, analytical and collaborative product leader who thrives on solving complex problems.
Exposure to energy management, industrial IoT or connected-building product categories.
Direct experience shipping AI or ML-powered features, including forecasting models, anomaly detection or conversational/LLM-based assistants, and communicating their capabilities and limits honestly to clients.
Familiarity with agile product development and data-driven experimentation.
Awareness of responsible AI practices relevant to enterprise B2B products, such as per-tenant data isolation, model risk considerations and honest disclosure of AI capability and certification status.
Key Performance Indicators
Delivery of product roadmap milestones on time and to quality.
Product adoption, usage and retention metrics against target.
Customer satisfaction and NPS for delivered features.
Revenue/ARR impact and business case realisation for major releases.
Time-to-market for new features and product launches.