Generative AI and Intelligent Systems Engineer – KTP Associate (26 Months Fixed Term)

Birmingham City University are looking to appoint a high calibre graduate as a Generative AI and Intelligent Systems Engineer (KTP Associate).

This role presents an exciting opportunity to work in collaboration with leading academics at Birmingham City University, to apply knowledge and technical innovation, delivered on site at the company.

This Knowledge Transfer Project (KTP) is co-funded by a grant from Innovate UK and Hockley Mint Limited. It is therefore essential you understand the fundamentals of the KTP collaboration between a UK business and a University works to deliver benefits for each (the company, the university, and the graduate).

Personal Training & Development Budget

The Generative AI and Intelligent Systems Engineer (KTP Associate) will have access to a wider range of benefits including a personal development budget of £4,333 to upskill during the project.

Location and Reporting

The successful candidate will be employed by Birmingham City University and seconded to work full-time onsite at Hockley Mint Limited, 65 – 66 Warstone Lane, Hockley, Birmingham, B18 6NG. The Generative AI and Intelligent Systems Engineer (KTP Associate) will deliver the 26-month KTP project in partnership Birmingham City University and Hockley Mint Limited.

The successful candidate will have full access to Birmingham City University’s resources such as offices, labs, and library to complete the KTP project (a project workplan written with KPIs and outcome deliverables has been written).

The Generative AI and Intelligent Systems Engineer (KTP Associate) will be supervised and mentored by both a lead academic and academic supervisor academics from BCU’s Department of Computer Science within the School of Architecture, Built Environment, Computing and Engineering (ABCE) as well as a company supervisor located at Hockley Mint Limited whose aim is to assist the Generative AI and Intelligent Systems Engineer (KTP Associate) to deliver the knowledge into Hockley Mint Limited and successfully deliver the 26-month KTP project on behalf of Hockley Mint Limited and Birmingham City University.

Main Duties and Responsibilities

The Generative AI and Intelligent Systems Engineer KTP Associate will work on:

• Designing the system architecture (presentation, application, data, integration layers).
• Developing multilingual conversational AI.
• Building NLP generative rendering pipelines.
• Developing AI-driven 3D generation and rendering systems.
• Designing and implementing ETL/data pipelines.
• Integrating AI systems into HM’s existing digital platforms.
• Conducting market analysis and business model redesign.
• Developing training materials and embedding knowledge within the company.
• Producing academic dissemination outputs (conference/journal papers).

The role requires the successful candidate to:

• Lead the technical direction of the KTP project.
• Operate as the interface between the university academics and company stakeholders.
• Translate outputs into commercially viable solutions.
• Work independently while managing project milestones and deliverables.
• Present technical progress to senior management.
• Main detailed documentation and version control.
• Ensure compliance with ethical AI and data governance standards.
• Deliver measurable business impact through innovation.

The Generative AI and Intelligent Systems Engineer (KTP Associate) will be expected to interact with the senior management, suppliers and clients of the company as well as BCU academics.

The Generative AI and Intelligent Systems Engineer (KTP Associate) must also be adept at applying their knowledge to commercial projects, driving value and making an impact where possible, with an ability to solve problems and create innovative solutions.

The Generative AI and Intelligent Systems Engineer (KTP Associate) must have the following key attributes to ensure the project’s successful completion.

Skills and Experience

The Generative AI and Intelligent Systems Engineer (KTP Associate) will hold a relevant degree. This might be a first degree (equivalent to a first class or 2:1 honours) in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a closely related discipline. A master’s degree in Artificial Intelligence, Machine Learning, Generative Ai, or a closely related field will be advantage.

Essential

• A minimum 2:1 undergraduate qualification in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a closely related discipline with a First Class or 2:1 Honours degree.
• Strong programming skills (Python essential).
• Experience with machine learning frameworks (e.g., PyTorch, TensorFlow).
• Experience with Large Language Models (LLMs) and NLP systems.
• Experience designing APIs and system architectures.
• Knowledge of cloud computing environments (AWS, GCP, Azure).
• Experience with data modelling and ETL pipelines.
• Strong analytical and problem-solving skills.
• Experience working on innovation-led projects.
• Ability to translate technical solutions into commercial applications.

Desirable

• Master’s degree or PhD (awarded or near completion) in Artificial Intelligence, Machine Learning, Generative AI, or a closely related discipline will be an advantage.
• Experience with generative AI (Diffusion models, CLIP, NeRF, 3D GANs).
• Knowledge of 3D rendering (WebGL, GLTF, mesh processing).
• Experience integrating Speech-to-Text systems.
• Experience with multi-agent AI frameworks (e.g., LangChain).
• Knowledge of Explainable AI (SHAP, LIME).
• Experience with CAD/CAM systems.
• Experience in manufacturing or digital commerce environments.
• Publication record in AI or software engineering.
• Academic acumen to enable successful reporting through research publications in academic journals and marketing/training materials.

On a personal note, the Associate should be enthusiastic, motivated, punctual, conscientious, trustworthy and work well within a team.

For further information please contact Gerald Feldman at Gerald.feldman@bcu.ac.uk or Essa Shahra at essa.shahra@bcu.ac.uk.

The project focuses on developing an AI-enabled adaptive recommender system to deliver a commercially deployable hyper-personalisation suite embedded within HM’s e-commerce platform. The project will leverage Large Language Models (LLMs), Multilingual NLP pipelines, and Genetic AI recommender systems and Explainable AI (XAI) techniques.