SMART Buildings R&D Engineer (KTP Associate)

You will work with data from building management systems (BMS), energy, environmental and occupancy systems, helping to integrate disparate sources into a coherent Digital Twin architecture. The role is practical and delivery-focused, with an emphasis on robust data pipelines, system integration and operational insight, rather than visualisation alone.

This is a hands-on role suited to someone who enjoys working with real assets and real data, and who is motivated by improving how buildings are understood, operated and maintained. You will collaborate with engineers, estates teams and digital specialists to ensure Digital Twin solutions are technically sound, scalable, secure and genuinely useful to end users.

The role offers the opportunity to work on complex buildings or estates, contribute to the evolution of Digital Twin platforms, and help shape how digital approaches support building performance, resilience and long-term value. We would particularly welcome applicants with industry experience in developing intelligent systems that support decision-making using supervised and unsupervised learning, and with a clear understanding of data in the context of physical systems as well as development of predictive analytics targeting the degradation of such systems.

The duties and responsibilities will include – sensor deployment and integration, and development of the data-pipeline/ infrastructure capable of supporting the realisation of data-enabled services for a wide variety of customers. The job involves interaction with the customers and their equipment base, mapping of their engineering and business challenges, articulation of the requirements for DT design and development, deployment of sensing capabilities, design and deployment of DT models and predictive analytics. The job also involves working very closely with the SOLIS Group’s IT manager to ensure the DT solutions meet the company’s and its customers’ cyber security requirements. Additional desirable experience includes managing data pipelines that involve data ingestion, transformation, integration, and cloud-based storage; deploying AI systems using cloud platforms (e.g., AWS, Azure, GCP), containerisation (Docker), API endpoints, and model inference optimisation; particularly in collaboration with senior leadership or communities to co-design solutions aligned with organisational needs of various customers.

The job will require an entrepreneurship mindset (awareness of commercialisation of Product-Service Systems/Software as a Service). It will often involve work (installation of sensing technologies, configuration of edge devices and communication infrastructure) and meetings at customers’ sites.

To develop, test, verify, and launch a Digital Twin platform to support the life span of physical assets by remotely monitoring their condition and health, which will enable proactive maintenance, service, and repair for commercial clients in the UK facilities management sector