Job Description
The CTO will be responsible for leading the technological vision and execution of 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, and managing the IT and analytics teams.
Key Responsibilities
Technology Leadership & Strategy
- 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.
AI/ML Model Deployment & Management & Gen AI
- Lead the design, development, deployment, and monitoring of predictive maintenance and energy optimization models.
- Ensure model explainability, accuracy, and continuous improvement through MLOps practices.
- Promote Gen AI agents.
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.
Team Leadership & Culture
- 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 clients 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.
