Engineer, AI

Job Description: - Collaborate closely with multidisciplinary teams—including engineering, operations, and quality assurance—to gather requirements and translate them into viable and user-friendly digital tools. - Assist in gathering, validating, and analysing data critical for pilot projects, ensuring accuracy and relevance to support performance monitoring and continuous improvement efforts. - Support end-to-end change management activities, including engaging users, creating comprehensive documentation, and training materials, and providing assistance during the rollout phases to ensure smooth adoption. - Ensure all digital solutions comply with organisational governance, cyber security policies, and operational standards to maintain integrity and reliability. - Support and actively contribute to continuous improvement programmes, focusing on digitalisation and automation initiatives aimed at streamlining workflows and enhancing operational efficiency. - Develop hands-on expertise by working on AI-assisted tools and automation frameworks, assisting in building predictive, data-driven applications that support informed decision-making. Job Requirements - Basic understanding of software development principles with practical experience or coursework in at least one programming language or development platform. - A proactive, self-motivated learner with the capacity to work independently and adapt to evolving priorities within a fast-paced and dynamic environment. - Strong communication skills paired with a collaborative mindset, enabling effective teamwork and stakeholder engagement. - Familiarity or experience in full-stack development covering both frontend and backend technologies. - An interest in or previous exposure to automation technologies, data analytics methodologies, AI-enabled systems, or low-code/no-code development platforms. - Ability to map and analyses operational processes and workflows, identifying opportunities for automation and system enhancements to eliminate inefficiencies. - Knowledge of enterprise data platforms, APIs, and systems integration. - Experience in Data Science and Machine Learning model development. Industry certifications in AI/ML, cloud, or enterprise architecture.