> Markdown version of [/jobs/ext/2912508-campus-full-time-ai-engineer-2027-uk-burgess-hill](https://www.wearedevelopers.com/jobs/ext/2912508-campus-full-time-ai-engineer-2027-uk-burgess-hill). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Campus - Full Time - AI Engineer - 2027 (UK - Burgess Hill) - **Company:** American Express - **Location:** Burgess Hill, UK - **Contract:** Internship / Graduate position - **Skills:** Java (Programming Language), JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Code Review, Collaborative Software, Computer Engineering, Continuous Integration, Information Engineering, Extract Transform Load (ETL), Data Retrieval, Data Structures, Software Debugging, Programming Tools, R (Programming Language), Python (Programming Language), Machine Learning, Language Modeling, Natural Language Processing, Object-Oriented Software Development, Scrum Methodology, Software Engineering, Supervised Learning, Data Processing, Cloud Platform System, Feature Engineering, Large Language Models, Prompt Engineering, Generative AI, Git, Information Technology, Free and Open-Source Software, Machine Learning Operations, Virtual Agents, Software Version Control, Data Pipelines, Unsupervised Learning - **Published:** September 15, 2026 - **Apply:** https://dejobs.org/x/x/495BF63A65884708839535C163C33F46/job/ ## About the Role * Must have earned a Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, Artificial Intelligence, Computer Engineering, Software Engineering, or another technical field before the full-time start date. * Students must have a graduation date between December 2026 and June 2027., * Knowledge of Python and foundational data processing technologies. * Foundational understanding of computer science concepts, including data structures, algorithms, object-oriented programming, debugging, testing, and problem solving. * Foundational understanding of machine learning concepts such as supervised learning, unsupervised learning, model training, evaluation, feature engineering, and experimentation. * Introductory understanding of modern AI systems, including LLM APIs, prompt-based interactions, retrieval patterns, AI powered tools, or generative AI applications. * Ability to support AI/ML development, testing, documentation, integration, or data pipeline activities under guidance. * Awareness of responsible AI expectations, including reliability, safety, governance, security, privacy, compliance, and appropriate escalation when work is unclear or outside standard guidance. * Strong communication, collaboration, documentation, and learning agility with the ability to work effectively across technical and non-technical teams., * Experience through academic coursework, research, projects, open-source contributions, internships, hackathons, or extracurricular activities using Python, R, Java, JavaScript, or similar technologies. * Interest in machine learning, generative AI, natural language processing, intelligent automation, data engineering, agentic AI, or AI-enabled software development. * Familiarity with NLP techniques and model concepts such as fuzzy matching, embeddings, BERT, transformers, LLMs, or other modern language models. * Exposure to LLM APIs or similar AI models, including prompt engineering, prompt evaluation, tools, function calling, retrieval patterns, or agent workflow concepts. * Experience or coursework involving machine learning algorithms and applying them to practical or real-world problems. * Familiarity with APIs, data pipelines, ETL processes, cloud environments, containerized development, model deployment patterns, or monitoring. * Awareness of CI/CD, version control, testing, code reviews, Agile development, and collaborative software engineering workflows. * Exposure to version control systems such as Git and collaborative software development workflows. * Curiosity for AI powered developer tools, responsible AI practices, governance, security, model documentation, and enterprise-scale delivery. ## Description * Support the development, testing, and integration of AI / ML models, LLM integrations, intelligent services, or data retrieval pipelines under guidance. * Assist with data collection, preprocessing, transformation, and validation to support model training, testing, evaluation, and implementation. * Contribute to debugging and improving AI enabled solutions to strengthen performance, reliability, explainability, maintainability, and quality. * Support AI capabilities such as model training workflows, inference endpoints, prompt-based interactions, evaluation routines, retrieval patterns, AI agents, or agentic workflows. * Collaborate with engineering, product, data, risk, security, and business partners to implement AI-driven solutions aligned to business requirements. * Document model parameters, prompts, assumptions, data pipelines, integrations, and technical decisions to support reproducibility and knowledge sharing. * Participate in Agile development practices, including sprint planning, stand-ups, demos, retrospectives, code reviews, and team ceremonies. * Assist in ensuring AI systems and AI-enabled features align with enterprise expectations for reliability, safety, governance, security, compliance, and appropriate escalation. ## Related Videos - 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