BD Manager / Project Manager (Enterprise Smart Building & AI Solution)
Salary: $25,000 – $37,000 per month
Role Overview
We are seeking an Enterprise Smart Building AI Consultant to guide enterprise clients through the strategy, design, and deployment of AI-driven building management solutions. In this role, you will bridge the gap between facility operations, corporate real estate (CRE) strategy, and cutting-edge artificial intelligence—helping organizations optimize energy efficiency, lower carbon footprints, improve occupant experience, and automate building operations.
Key Responsibilities
Strategic Advisory: Lead discovery workshops with enterprise executives, CRE leaders, and facility heads to identify high-value AI use cases across energy optimization, predictive maintenance, space utilization, and occupant wellness.
Architecture & Solution Design: Evaluate client OT/IT infrastructure (BMS, IoT sensors, SCADA, ERP) to architect scalable AI/ML solutions (e.g., predictive HVAC control, occupancy analytics, automated fault detection and diagnostics).
Vendor & Integration Guidance: Help clients select and integrate best-in-class Smart Building AI platforms, IoT edge devices, and cloud services (AWS, Azure, GCP).
ROI & Business Case Development: Build financial models, ROI projections, and sustainability frameworks (Scope 1 & 2 emissions reduction, LEED/WELL alignment) to justify project investments.
Project Oversight & Delivery: Partner with system integrators, data scientists, and facilities engineering teams to oversee implementation, ensuring models deliver promised operational KPIs.
Change Management: Facilitate adoption across client organizations by delivering technical roadmaps, stakeholder alignment, and operator training.
Qualifications
Experience: 5+ years in technical consulting, solution architecture, or digital transformation within smart buildings, CRE tech, or industrial IoT.
Domain Expertise: Deep understanding of Building Management Systems (BMS/BAS—Siemens, Honeywell, Schneider Electric, Johnson Controls), IoT edge architectures, and HVAC/MEP systems.
AI/ML Proficiency: Solid grounding in practical AI applications (time-series forecasting, predictive maintenance, anomaly detection, reinforcement learning for energy optimization).
Data Integration: Familiarity with building protocols and data standards (BACnet, Modbus, MQTT, Haystack, RealEstateCore).
Client-Facing Skills: Proven track record of presenting complex technical concepts to C-suite and non-technical stakeholders.
Preferred Qualifications
Certifications in sustainability or facilities management (CEM, LEED AP, WELL AP).
Background in data science or software engineering.
Experience with ESG framework reporting (GRESB, CDP).