Whether you are a recent university graduate or have up to two years of relevant experience, this role provides an exceptional opportunity to build a career at the forefront of Data, Artificial Intelligence, and Digital Transformation.
As part of our Data, AI & Emerging Technology team, you will work alongside data engineers, software engineers, AI specialists, solution architects, and business consultants to help organisations solve complex business challenges using modern technologies. You will contribute to the design and development of cloud-based data platforms, AI-enabled solutions, intelligent automation capabilities, and software applications that create measurable business value. This role offers exposure to cutting-edge technologies including Generative AI, Machine Learning, Data Platforms, Cloud Engineering, Intelligent Automation, and Software Development, while working with leading organisations across multiple industries. What You Will Do Data Engineering & Modern Data Platforms - --Design, build, and maintain scalable data pipelines and data integration solutions. -Develop ETL/ELT processes to ingest, transform, and orchestrate data from multiple sources. -Support the implementation of modern cloud-based data platforms and data warehouses. -Ensure data quality, reliability, governance, and security across data ecosystems. -Assist in modelling and structuring data to support analytics, reporting, and AI use cases. -Participate in data migration and modernisation initiatives. Artificial Intelligence & Machine Learning - -Support the development and deployment of AI and Machine Learning solutions. -Assist in preparing, cleansing, and engineering datasets used for predictive analytics and AI models. -Contribute to the development of Generative AI solutions using Large Language Models (LLMs). -Support the implementation of AI-powered assistants, copilots, chatbots, and intelligent automation solutions. -Participate in prompt engineering, model evaluation, testing, and performance optimisation activities. -Help implement Responsible AI practices, including model monitoring, explainability, and governance controls. -Collaborate with data scientists and AI specialists to operationalise models into production environments. -Software Engineering & Solution Development -Design, develop, test, and maintain software applications, APIs, and microservices. -Contribute to full-stack, backend, or integration development activities depending on project requirements. -Participate in agile software development practices, including sprint planning, stand-ups, code reviews, and retrospectives. -Develop reusable components, accelerators, and automation solutions. -Apply software engineering best practices, including version control, testing, security, and performance optimisation. -Support CI/CD pipelines and deployment automation processes. Client Advisory & Project Delivery - -Work closely with clients to understand business challenges and technical requirements. -Participate in workshops, discovery sessions, and solution design activities. -Translate business requirements into scalable technology solutions. -Support project delivery teams across data, AI, and digital transformation engagements. -Prepare technical documentation, demonstrations, and solution presentations. -Collaborate with multidisciplinary teams to deliver high-quality outcomes. -Innovation & Continuous Learning -Stay current with emerging trends in AI, data engineering, software engineering, and cloud technologies. -Contribute to innovation initiatives, proof-of-concepts, and internal capability development. -Participate in hackathons, innovation challenges, and thought leadership activities. -Support the development of assets and accelerators that enhance client delivery. What We're Looking For Education Bachelor's or Master's degree (completed or in progress) in Computer Science, Software Engineering, Data Science, Artificial Intelligence, Information Systems, Mathematics, Engineering, or a related field. Outstanding final-year students and recent graduates are strongly encouraged to apply. Technical Skills Candidates should possess knowledge or experience in some of the following areas: Data & Analytics SQL and relational databases. Data modelling and data warehousing concepts. Data integration, ETL/ELT, and data transformation. Data visualisation and analytics fundamentals. Programming & Software Development Python, Java, C#, JavaScript, or similar programming languages. Understanding of object-oriented programming principles. API development and system integration concepts. Git and version control practices. Software testing and debugging techniques. AI & Machine Learning Understanding of Machine Learning fundamentals. Familiarity with Generative AI concepts and Large Language Models. Knowledge of prompt engineering and AI application development is advantageous. Exposure to machine learning libraries such as Scikit-Learn, TensorFlow, PyTorch, LangChain, or similar technologies is beneficial. Cloud & Modern Technologies Exposure to Microsoft Azure, AWS, or Google Cloud. Understanding of containerisation technologies such as Docker and Kubernetes is advantageous. Familiarity with Databricks, Microsoft Fabric, Snowflake, Synapse, MuleSoft, or similar platforms is considered a plus. The Ideal Candidate You are someone who: Has a passion for building technology solutions that solve real business problems. Is excited by the rapidly evolving world of Artificial Intelligence and Data. Enjoys both software engineering and analytical problem-solving. Demonstrates curiosity, creativity, and a continuous learning mindset. Thrives in collaborative and fast-paced environments. Has strong communication and interpersonal skills. Is comfortable engaging with both technical and non-technical stakeholders. Takes ownership and consistently looks for opportunities to improve and innovate. What We Offer The opportunity to work on high-impact Data, AI, and Digital Transformation programmes. Hands-on experience with leading AI, cloud, and data technologies. Structured learning, mentoring, and professional certification pathways. Exposure to senior client stakeholders and industry experts. Collaboration with multidisciplinary teams across technology, strategy, risk, and business advisory. Continuous investment in technical and professional development. Competitive remuneration and performance-based rewards. A flexible and inclusive working environment that encourages innovation.
If multiple Education and Language Profiles are defined, please note that you must fit at least one of them, but not necessarily all.
| Subject | Level | Grade |
|---|---|---|
| ARTIFICIAL INTELLIGENCE | ||
| MATHEMATICS | ||
| ENGINEERING |
