AI Specialist

Role Summary The AI Specialist will support the identification, evaluation, and implementation of practical AI solutions across the business. Working with business teams, IT, and external partners, the role will explore AI opportunities, assess available tools and models, support pilot initiatives, and promote the responsible use of AI. The role requires curiosity, strong research skills, and the ability to learn and experiment. Coding knowledge is useful as a technical background for prototyping and solution assessment, but it is not the main focus of the position. Role & Responsibilities AI Solutions & Innovation • Explore AI tools, models, agents, and platforms and assess their relevance to business needs. • Research and recommend practical AI solutions that can improve productivity, quality, efficiency, or decision-making. • Understand business challenges and help translate them into clear AI use cases. • Support the development, testing, and evaluation of small AI pilots and proofs of concept. • Compare solutions based on usability, accuracy, security, integration, cost, and expected business value. • Help configure and implement approved AI solutions using available platforms and tools. • Work with departments to understand their processes, challenges, repetitive work, and improvement opportunities. • Stay up to date with developments in AI tools, models, automation, and digital technologies. • Support the secure and responsible use of AI in line with company policies and approved controls. • Prepare clear documentation, user guides, presentations, and progress updates. • Support AI awareness sessions, demonstrations, and knowledge-sharing activities across the organization. Business Engagement & AI Adoption • Help departments identify and document practical AI opportunities. • Support the evaluation and prioritisation of use cases based on value, feasibility, data availability, risk, and effort. • Gather user feedback and help improve solutions during pilots. • Explain AI capabilities and limitations in clear business language. • Encourage adoption of approved AI tools and responsible working practices. Project & Pilot Coordination • Support the planning and coordination of AI initiatives and pilot projects. • Track activities, timelines, deliverables, risks, and decisions. • Coordinate with internal teams, business owners, vendors, and external specialists where required. • Help define pilot success measures and monitor outcomes. • Document lessons learned and recommendations on whether a pilot should be improved, scaled, or stopped. Documentation, Responsible Use & Continuous Learning • Maintain clear and practical documentation for AI use cases, pilots, solutions, and user guidance. • Prepare simple progress reports covering outcomes, issues, risks, and next steps. • Follow company requirements for security, privacy, data protection, human review, and responsible AI use. • Continuously research and test new AI capabilities and share useful findings with the team. • Build personal knowledge through practical experimentation, training, certifications, and industry learning. • Share knowledge through demonstrations, short guidance sessions, and reusable examples. Candidate Requirements • Good understanding of modern AI tools, models, agents, and their practical business applications. • Familiarity with tools such as Microsoft Copilot, ChatGPT, Claude, Gemini, Copilot Studio, Power Platform, or similar technologies. • Strong interest in AI and the ability to research, explore, compare, and quickly learn new technologies. • Good analytical, problem-solving, and experimentation skills. • Ability to understand business processes and identify practical improvement opportunities. • Good communication and presentation skills, with the ability to explain AI in simple language. • Ability to work collaboratively with technical and non-technical teams. • Basic understanding of data, reporting, security, privacy, and responsible AI use. • Good documentation, organisation, and follow-up skills. Technical Knowledge | Preferred • Familiarity with Microsoft 365, including Copilot, SharePoint, Power Automate, Power Apps, Teams, Power BI, and Copilot Studio. • Basic knowledge of Python, SQL, APIs, JavaScript, C#, or another programming or scripting language. • Ability to understand, test, and make minor changes to code where required. • Understanding of large language models, prompting, AI agents, automation, data sources, and system integration. • Experience building simple prototypes, automations, or AI-assisted solutions is an advantage. • Exposure to Microsoft Azure or another cloud platform is beneficial. • Experience with advanced machine learning libraries such as TensorFlow or PyTorch is an advantage, not a requirement. Candidate Qualifications • Bachelor’s degree in computer science, Information Systems, Artificial Intelligence, Data Science, Software Engineering, or a related field. • Approximately three years of relevant experience in technology, AI, automation, software, digital solutions, or a related area. • Practical experience using modern AI tools for research, productivity, prototyping, or business improvement. • Experience supporting technology initiatives, pilots, or cross-functional projects is preferred. • Relevant Microsoft, AI, cloud, data, or automation certifications are an advantage. Show more Show less

Bachelor’s degree in computer science, Information Systems, Artificial Intelligence, Data Science, Software Engineering, or a related field. Approximately three years of relevant experience in technology, AI, automation, software, digital solutions, or a related area. Practical experience using modern AI tools for research, productivity, prototyping, or business improvement. Experience supporting technology initiatives, pilots, or cross-functional projects is preferred. Relevant Microsoft, AI, cloud, data, or automation certifications are an advantage.

AI Solutions & Innovation: Explore AI tools, models, agents, and platforms and assess their relevance to business needs. Research and recommend practical AI solutions that can improve productivity, quality, efficiency, or decision-making. Understand business challenges and help translate them into clear AI use cases. Support the development, testing, and evaluation of small AI pilots and proofs of concept. Compare solutions based on usability, accuracy, security, integration, cost, and expected business value. Help configure and implement approved AI solutions using available platforms and tools. Work with departments to understand their processes, challenges, repetitive work, and improvement opportunities. Stay up to date with developments in AI tools, models, automation, and digital technologies. Support the secure and responsible use of AI in line with company policies and approved controls. Prepare clear documentation, user guides, presentations, and progress updates. Support AI awareness sessions, demonstrations, and knowledge-sharing activities across the organization. Business Engagement & AI Adoption: Help departments identify and document practical AI opportunities. Support the evaluation and prioritisation of use cases based on value, feasibility, data availability, risk, and effort. Gather user feedback and help improve solutions during pilots. Explain AI capabilities and limitations in clear business language. Encourage adoption of approved AI tools and responsible working practices. Project & Pilot Coordination: Support the planning and coordination of AI initiatives and pilot projects. Track activities, timelines, deliverables, risks, and decisions. Coordinate with internal teams, business owners, vendors, and external specialists where required. Help define pilot success measures and monitor outcomes. Document lessons learned and recommendations on whether a pilot should be improved, scaled, or stopped. Documentation, Responsible Use & Continuous Learning: Maintain clear and practical documentation for AI use cases, pilots, solutions, and user guidance. Prepare simple progress reports covering outcomes, issues, risks, and next steps. Follow company requirements for security, privacy, data protection, human review, and responsible AI use. Continuously research and test new AI capabilities and share useful findings with the team. Build personal knowledge through practical experimentation, training, certifications, and industry learning. Share knowledge through demonstrations, short guidance sessions, and reusable examples.