The CTO will be responsible for leading the technological vision and execution AI-driven solutions for industrial efficiency. This includes overseeing the deployment of ML/AI models and GEN AI, promoting product mindset, maintaining and scaling infrastructure, ensuring cybersecurity compliance, managing the IT and analytics teams. Key Responsibilities Define and execute the long-term technology roadmap aligned with business objectives. Select, evaluate, and implement best-fit technologies, frameworks, and tools for scalability and security Ensure compliance with U.S. and international cybersecurity standards for SaaS and on-premise deployments. Lead the design, development, deployment, and monitoring of predictive maintenance and energy optimization models. Ensure model explainability, accuracy, and continuous improvement through MLOps practices. Infrastructure & IT Management Oversee integration with customer data sources (SCADA, historians, ERP, IoT platforms). Promoting APIs to facilitate integration and scalability. Manage and scale cloud infrastructure to support industrial clients with high reliability and security. Define DevOps/MLOps processes, CI/CD pipelines, and monitoring frameworks. Oversee IT operations, data protection, and compliance. Build, mentor, and manage the engineering, data science, and IT teams. Foster a culture of innovation, collaboration, and accountability aligned with the company values. Collaborate cross-functionally with Product, Sales, and Customer Success teams. Stakeholder Engagement Communicate technology strategy and progress to executive leadership, board, and investors. Engage with customers and partners to understand technical requirements and translate them into scalable solutions. Representation in technical forums, industry events, and with potential investors. Qualifications Education: Bachelor’s or Master’s in Computer Science, Engineering, Data Science, or related field (PhD a plus). Experience 8+ years in software engineering, data science, or IT, with at least 3–5 years in leadership roles. Proven track record in deploying ML/AI models in production at scale. Experience with SaaS platforms for industrial/energy/manufacturing client is highly desirable. Technical Skills Proficiency in ML frameworks (TensorFlow, PyTorch, Scikit-learn). Strong knowledge of cloud platforms (AWS) solution deployments. Familiarity with industrial protocols (OPC-UA, Modbus, MQTT) a plus. Experience in DevOps/MLOps, containerization (Docker, Kubernetes), and CI/CD. Solid understanding of cybersecurity, data privacy, and compliance requirements. Leadership Skills Strategic thinker with hands-on execution capabilities. Strong communicator able to bridge business and technical worlds. Experience building and managing high-performance teams. #J-18808-Ljbffr