About the Role

We are seeking an AI Scientist to drive innovation in next-generation AI systems, with a strong focus on large language models (LLMs), generative AI, agentic AI, and advanced data technologies. This role sits within a dedicated prototyping environment, working on cutting-edge AI, connectivity, communications, and trust technologies. You will be involved in hands-on experimentation and development, rapidly turning concepts into working prototypes.

Key Responsibilities

• Lead the end-to-end prototyping lifecycle for data and AI systems, from concept design to Proof-of-Concept development.
• Develop and refine AI prototypes using novel techniques, with emphasis on LLM development, fine-tuning, optimisation, and real-world integration.
• Produce clear, detailed technical documentation for experiments and prototypes.
• Support and run innovation challenge activities to surface new ideas and prototype approaches.
• Contribute technical thought leadership through papers, blogs, and presentations on AI best practices.
• Participate in demos, technical showcases, and internal knowledge-sharing sessions.
• Engage with global research and industry partners to stay current with emerging trends and represent the team at international forums.

Requirements

You should have at least 5 years of experience in two or more of the following domains:

AI Product Engineering / Prototyping

• Translating real-world problems into AI/ML problem statements.
• Building ML/LLM models using modern AI libraries and techniques.
• Deploying AI workflows to enhance product development or operational processes.
• Assessing the effectiveness, scalability, and sustainability of AI workflows.

Data Engineering

• Hands-on experience with data collection, ingestion, storage, transformation, and pipeline design.
• Ability to map complex data sources, design data flows, and integrate multiple streams into usable datasets.
• Familiarity with data management and optimisation practices.

AI Ethics & Governance

• Applying ethical guidelines and governance frameworks in AI development.
• Ensuring responsible and compliant use of AI in projects.

Additional Attributes

• Experience commercialising or translating emerging technologies into practical applications.
• Strong understanding of the practical limitations and challenges in AI and data systems.
• Passion for hands-on experimentation and rapid prototyping.
• Interest or experience in LLM development, model fine-tuning, agentic workflows, or generative AI applications.