Product Lead — IoT & Digital Twin Platform

Job Description:

We are building the next-generation smart facilities platform — one that goes far beyond traditional BMS.

At its core is a live digital twin of every building we deploy in a real-time, physics-informed virtual replica of its mechanical, electrical, and environmental systems.

This role is for a hands-on Product Lead who can both architect and lead. You will own the full stack from edge device to cloud analytics, define product direction, and mentor a growing engineering team.

If you have deep expertise at the intersection of IoT, controls, and scalable software — and are excited by the idea of buildings that think — this role is for you.

Responsibilities

• End-to-end platform architecture:

• Edge → Gateway → Cloud / On-Prem → Analytics → Control feedback loop

• Digital Twin Development:

• Build and maintain real-time building digital twins using physics-based and data-driven models

• Model HVAC topology, asset hierarchies, and operational states in a live twin environment

• Integrate BIM data, sensor streams, and historical operations data into the twin

• Protocol & Systems Integration:

• BACnet, Modbus, OPC-UA, MQTT — connecting real building systems to the platform

• Real-time data ingestion pipelines and time-series analytics engines

• Control strategy development:

• HVAC optimization, demand response, fault detection

• Product thinking: translate facility-level problems into software abstractions and roadmap

• Mentor and lead a team of 5–6 engineers across backend, integration, and analytics

• Education and Experience:

• 5+ years in IoT / Industrial IoT / Building Automation platforms

• Deep understanding of HVAC systems: chillers, AHUs, VAVs, VRF, cooling towers

• Hands-on experience with BACnet, Modbus, OPC-UA, MQTT

• Digital Twin experience:

• Building or industrial digital twin platforms (e.g., Azure Digital Twins, AVEVA, Siemens Xcelerator, custom)

• Working knowledge of twin modelling concepts: ontologies, asset graphs, state synchronization

• Strong backend engineering in Python — the primary language for data pipelines, analytics, and AI integration

• AI & Machine Learning Integration:

• Experience embedding AI/ML models into production systems: predictive maintenance, anomaly detection, load forecasting

• Familiarity with LLM APIs (OpenAI, Anthropic) or AI orchestration frameworks (LangChain, LlamaIndex) for building intelligent features

• Experience with time-series databases: InfluxDB, TimescaleDB, or similar

• Proven ability to lead engineering teams and drive product decisions