Senior AI Software Engineer (VP)

As a Senior AI Software Engineer, you will play a key role in designing, developing, and implementing intelligent software solutions that drive innovation, improve engineering productivity, and deliver measurable business value. You will work closely with AI Architects, Data Engineers, Data Scientists, Product teams, and Engineering colleagues to build scalable, secure, and production-ready AI systems and applications.

You will have strong knowledge of Generative AI, AI-assisted code generation, automated testing, code review acceleration, agentic workflows, and development process optimisation. This role involves providing technical leadership, engineering expertise, and tooling oversight across the software delivery lifecycle, helping teams apply AI responsibly to modernise platforms, improve code quality, streamline delivery, and enhance developer experience across cloud platforms and technology products.

 

To be successful as a Senior AI Software Engineer, you should possess:

• Programming and Software Engineering skills – Develop, integrate, and maintain AI-enabled software solutions using languages such as Python, Java, R, and C++, applying strong software engineering principles, clean coding practices, API design, distributed computing, UNIX tooling, and scalable system design.
• Machine Learning and AI Fundamentals – Solid knowledge of supervised and unsupervised learning, neural networks, model evaluation, prompt engineering, code transformation and refactoring, data transformation and schema conversion, automated test case generation, and responsible AI practices.
• Data Handling and Analysis experience – Ability to work with large and complex datasets, including data preprocessing, feature engineering, data quality assessment, vectorisation, embeddings, and the effective use of data science and machine learning libraries.
• AI Engineering and Product Delivery – Experience building AI-powered capabilities into production applications, balancing experimentation with robust engineering, security, observability, maintainability, and customer impact.

 

Additional skills include:

• Automation and Tooling Management – Expertise in tooling selection, developer productivity tooling, Infrastructure as Code tools such as Terraform and Ansible, CI/CD implementation, automated quality controls, and engineering workflow optimisation.
• Cloud and Deployment Knowledge – Familiarity with deploying AI models and AI-enabled services using cloud platforms such as AWS, Azure, or GCP, MLOps practices, cloud architecture, containerisation, model monitoring, and secure production deployment patterns.
• Problem-Solving and Communication skills – Ability to translate complex business and engineering challenges into practical AI solutions, explain technical outcomes clearly to both technical and non-technical stakeholders, and support effective technical planning, implementation, and adoption.

 

You may be assessed on key critical skills relevant for success in role, such as risk and controls, communication skills and interaction with a diverse range of stakeholders, as well as job-specific technical skills.

 

This role is based out of our Knutsford office.