Graduate AI Engineer

About Allica Bank

Allica is the UK’s fastest growing company - and the fastest-growing financial technology (Fintech) firm ever. Our purpose is to help established SMEs, one of the last major underserved opportunities in Fintech.

Established SMEs are the backbone of local communities - representing over a third of our economy - yet have been largely neglected both by traditional high street banks and modern fintech providers.

Our Engineering team is part of the wider organisation and is responsible for building products and technology solutions that create value across the business. We work closely with Product Managers and Designers to identify opportunities, solve customer and business challenges, and deliver high-quality products and experiences. Through collaboration, experimentation, and continuous improvement, we build solutions that support teams across the organisation and help drive meaningful outcomes.

We're looking for exceptional graduates who are excited by the opportunity to learn, contribute, and help build the next generation of products and capabilities.

As a Graduate AI Engineer, you'll join a team building and deploying AI solutions in our Autonomous Lending Tribe. This role is ideal for someone who has recently graduated from a leading university and is excited about applying Generative AI, Machine Learning, and modern software engineering practices to solve real business problems.

You may not have extensive industry experience yet, but you have demonstrated your capabilities through academic projects, internships, hackathons, research, open‑source contributions, or personal projects. As a Graduate AI Engineer, you'll work closely with experienced engineers, product managers, and business stakeholders to design, build, and deploy AI solutions that create meaningful impact. You'll have the opportunity to work across the full lifecycle—from experimentation and prototyping through to production deployment and monitoring.

• AI Application Development
• Build AI‑powered applications using Large Language Models (LLMs) and modern AI frameworks.
• Develop Retrieval‑Augmented Generation (RAG) solutions using vector databases, embeddings, and document retrieval techniques.
• Experiment with prompt engineering, agent workflows, and emerging AI capabilities.
• Build backend services and APIs that power AI applications.
• Contribute to frontend applications using React.js or similar technologies.
• Write clean, maintainable, and well‑tested code.

• Work closely with product and engineering teams to understand customer problems and develop AI‑driven solutions.
• Rapidly prototype ideas and iterate based on feedback and real‑world usage.
• Contribute to the end‑to‑end delivery of AI features from concept through deployment.

• Stay current with developments in Generative AI, Machine Learning, and software engineering.
• Evaluate new tools, frameworks, and approaches that could improve our products and engineering practices.
• Participate in technical discussions and contribute ideas across the team.

• Curiosity and a genuine passion for technology and AI.
• A builder mindset with a desire to create products that people use.
• Ownership and accountability.
• Strong problem‑solving ability and analytical thinking.
• A willingness to learn quickly and embrace feedback.
• Excellent communication and collaboration skills.
• Comfort working in fast‑moving and evolving environments.

• Bachelor’s or Master’s degree in computer science, Artificial Intelligence, Machine Learning, Software Engineering, Mathematics, or a related field from a reputable university.
• Strong understanding of Machine Learning fundamentals and the AI development lifecycle.
• Experience building AI, Machine Learning, or Generative AI projects through academic work, internships, hackathons, research, open‑source contributions or personal projects.
• Strong programming skills in Python.
• Understanding of Large Language Models (LLMs), prompt engineering, and Generative AI concepts.
• Familiarity with Retrieval‑Augmented Generation (RAG), embeddings, and vector databases.
• U…