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Role Overview The Software Engineer (R&D) designs, develops and delivers robust, scalable software solutions while also originating and assessing new innovations. The role requires strong computer science foundations, the ability to think abstractly, and experience building performant core algorithms. The Software Engineer (R&D) works independently on complex technical tasks, collaborates effectively within Agile teams, and contributes across the full software development lifecycle. They are expected to mentor junior Engineers, contribute to architectural direction, and drive quality and innovation through best practices. In addition to core product development, the role may involve: R&D investigations and prototyping that feed into future products On project basis work within a two-week sprint Scrum framework Professional services projects for specific customers Supporting customers through advanced technical problem-solving and bug resolution Key Responsibilities R&D and Innovation Originate, prototype and assess new innovations Think abstractly to explore algorithms and approaches for calculating distances, performance and accuracy. Explain problems addressed and approach to them, listen and appreciate feedback Prototype ideas in code, design and run appropriate performance and correctness tests (including O(n) analysis). Call time on investigations that are not producing results and refocus effort where appropriate. Roadmap architectural approaches that address diverse and sometimes unconnected customer feedback. Ensure R&D work remains focused on clear goals and outcomes. Document findings thoroughly and hand over validated work to the wider development team. Demonstrable knowledge and experience in data mining, machine learning (including deep learning), generative AI (e.g., with Retrieval-Augmented Generation), and reinforcement learning. Software Development & Delivery Design, develop, test and maintain software applications using Java (8+), XSLT, XML, JSON, JavaScript, TypeScript and React . Develop and maintain automated tests to ensure high coverage, performance and reliability. Take ownership of feature development from concept through deployment. Write clean, maintainable and well-documented code following industry best practices. Submit code for CI pipelines, resolve broken builds, and actively participate in debugging and optimisation. Participate in code reviews, providing constructive feedback and mentoring junior Engineers. Data Science algorithms and techniques. Probability & Statistics. Parsing frameworks. Deeper knowledge of AI techniques beyond assembling predefined components. Background in theory of the techniques and maths that AI uses. Collaboration & Agile Ways of Working Actively participate in Agile ceremonies including Daily Scrum, Sprint Planning, Reviews and Retrospectives. Work closely with Product Management to understand customer feedback and prioritise areas for innovation. Collaborate across Engineering, Product and R&D to define and deliver new features. Contribute to backlog refinement and continuous improvement of team processes and technical practices. Customer & Operational Support Collaborate with internal support teams to deliver accurate solutions and improve customer satisfaction. Maintain accurate records of development work, R&D investigations, failed attempts and time spent. Keep JIRA issues and project documentation up to date. Required Skills & Experience Degree in Computer Science, Software Engineering , or equivalent professional experience. 3+ years experience in a major programming language, with strong experience writing core algorithms. Advanced proficiency in Java (8+) . Good knowledge of XSLT and data transformation techniques. Experience working with structured data formats such as XML and JSON. Strong understanding of algorithms, data structures and performance analysis (O(n . Experience with REST APIs , SaaS architectures and cloud infrastructure (preferably AWS). Hands-on experience with Git , Bitbucket, JIRA and Confluence. Familiarity with Agile/Scrum methodologies. Ability to work independently, lead technical initiatives, and collaborate effectively within teams. Desirable Experience XML comparison, transformation or document-processing systems. CI/CD pipelines and automated testing frameworks. Containerisation technologies such as Docker or Kubernetes. Data science algorithms, probability and statistics. Parsing frameworks. Deeper understanding of AI techniques and their mathematical foundations. Experience with JavaScript, TypeScript and React . JF1