As a Lead AI Engineer, you will design, develop, and deploy AI-driven solutions for smart buildings and industrial automation systems. Your work will focus on optimizing HVAC, lighting, security, energy management, and industrial processes using advanced machine learning, IoT integration, and predictive analytics. You will lead a team to deliver scalable AI solutions that enhance efficiency, sustainability, and operational reliability, while fostering a culture of innovation and continuous improvement.

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Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.

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As a Lead AI Engineer at Honeywell, you will lead and guide a team of AI engineers, providing technical expertise and support to successfully execute AI projects, driving innovation and contributing to the development and implementation of cutting-edge AI solutions.

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• Technical Expertise
  • Strong proficiency in Python, TensorFlow/PyTorch, and data science libraries.
  • Experience with IoT and industrial protocols (BACnet, Modbus, MQTT, OPC-UA).
  • Knowledge of control systems, HVAC, energy optimization, and industrial automation principles.
• AI/ML Knowledge
  • Expertise in supervised/unsupervised learning, time-series forecasting, and reinforcement learning.
  • Familiarity with anomaly detection and predictive maintenance algorithms.
• Industrial Automation
  • Hands-on experience with SCADA systems, PLC programming basics, and industrial process optimization.
  • Understanding of Industry 4.0 concepts and smart factory technologies.
• Innovation Skills
  • Ability to identify emerging trends and translate them into practical solutions.
  • Experience in rapid prototyping, proof-of-concept development, and technology scouting.
  • Strong problem-solving mindset with a focus on creative and disruptive solutions.
• Cloud & Edge Computing
  • Experience with AWS, Azure, or Google Cloud for AI deployment.
  • Understanding of edge devices and real-time inference.
• Leadership
  • Proven ability to lead technical teams and manage complex projects.
• Education
  • Bachelor’s or Master’s in Computer Science, Electrical Engineering, or related field (PhD preferred).

Preferred Experience

• 8+ years in AI/ML development, with at least 3 years in building or industrial automation.
• Experience in smart building platforms, SCADA systems, and energy management solutions.
• Track record of delivering innovative AI solutions in automation domains.

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• AI Solution Design & Development
  • Architect and implement AI/ML models for predictive maintenance, energy optimization, process automation, and anomaly detection in building and industrial systems.
  • Develop algorithms for real-time decision-making using sensor, IoT, and industrial control data.
• System Integration
  • Integrate AI solutions into Building Management Systems (BMS) and Industrial Control Systems (ICS), including SCADA and PLC environments.
  • Ensure interoperability with IoT devices, industrial protocols, and edge computing frameworks.
• Data Engineering
  • Design pipelines for collecting, cleaning, and processing large-scale building and industrial data (temperature, occupancy, energy usage, machine performance).
  • Implement scalable data storage and retrieval systems.
• Innovation & Research
  • Drive innovation by exploring emerging technologies such as generative AI, digital twins, and autonomous control systems.
  • Identify opportunities for applying AI to new use cases in smart buildings and industrial automation.
  • Lead proof-of-concept projects and pilot programs to validate innovative ideas.
• Performance Optimization
  • Apply reinforcement learning or adaptive control for dynamic building and industrial environments.
  • Continuously monitor and improve AI models for accuracy, efficiency, and reliability.
• Leadership & Collaboration
  • Lead a team of AI engineers and data scientists.
  • Work with product managers and stakeholders to define AI strategy for smart buildings and industrial automation.
• Compliance & Security
  • Ensure AI solutions adhere to cybersecurity standards and industrial safety protocols.
  • Maintain compliance with energy regulations and industry standards.