Solar Energy Systems Engineers

Perform site-specific engineering analysis or evaluation of energy efficiency and solar projects involving residential, commercial, or industrial customers. Design solar domestic hot water and space heating systems for new and existing structures, applying knowledge of structural energy requirements, local climates, solar technology, and thermodynamics.

The occupation of Solar Energy Systems Engineers has an automation risk of 52.9%. This risk is closely aligned with its base risk of 53.8%, reflecting the profession's mixture of both automatable and resistant tasks. The main reason for this moderate risk is that many functions within the role are process-oriented and involve data collection, analysis, and design, which are areas where AI and automated systems are continually advancing. For instance, the use of machine learning to optimize energy system layouts or computer vision to scan and assess sites has made it increasingly feasible for technology to take over significant parts of the job. As automation technology improves, especially in design software and site assessment tools, more tasks within this occupation are likely to become automatable. Among the tasks most susceptible to automation are those that follow logical and repeatable processes. The top three automatable tasks are conducting engineering site audits to collect information for solar power system design, creating plans for solar energy system development and evaluation, and designing or coordinating the design of photovoltaic (PV) or solar thermal systems for various buildings. These tasks are highly structured and can be efficiently performed by advanced algorithms and specialized software, often yielding faster and more error-free results than manual work. Automated drones and sensors can now perform site audits, design software can generate optimal layouts, and project management systems can plan and monitor activities, collectively reducing the need for human intervention in these areas. In contrast, several tasks remain resistant to automation due to the need for higher-level thinking and complex problem solving. Tasks such as designing or developing vacuum tube collector systems, testing or evaluating PV cells or modules, and performing in-depth analyses like thermal, stress, or cost reduction studies currently demand specialized expertise and adaptability. These areas require a significant degree of originality and innovative thinking, which are reflected in bottleneck skill metrics—such as originality, which rates at 3.5% and 3.9% for this occupation. Such skills are challenging for machines to replicate, as they require creativity, cross-disciplinary understanding, and nuanced judgment. Consequently, while many routine tasks can be automated, the engineering profession still relies on human ingenuity to solve novel challenges and drive technological progress.