Senior AI Software Engineer
AI in this role
Purpose of the role
To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues.
Accountabilities
- Development and delivery of high-quality software solutions by using industry aligned programming languages, frameworks, and tools. Ensuring that code is scalable, maintainable, and optimized for performance.
- Cross-functional collaboration with product managers, designers, and other engineers to define software requirements, devise solution strategies, and ensure seamless integration and alignment with business objectives.
- Collaboration with peers, participate in code reviews, and promote a culture of code quality and knowledge sharing.
- Stay informed of industry technology trends and innovations and actively contribute to the organization’s technology communities to foster a culture of technical excellence and growth.
- Adherence to secure coding practices to mitigate vulnerabilities, protect sensitive data, and ensure secure software solutions.
- Implementation of effective unit testing practices to ensure proper code design, readability, and reliability.
Vice President Expectations
- To contribute or set strategy, drive requirements and make recommendations for change. Plan resources, budgets, and policies; manage and maintain policies/ processes; deliver continuous improvements and escalate breaches of policies/procedures..
- If managing a team, they define jobs and responsibilities, planning for the department’s future needs and operations, counselling employees on performance and contributing to employee pay decisions/changes. They may also lead a number of specialists to influence the operations of a department, in alignment with strategic as well as tactical priorities, while balancing short and long term goals and ensuring that budgets and schedules meet corporate requirements..
- If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver to a consistently excellent standard. The four LEAD behaviours are: L – Listen and be authentic, E – Energise and inspire, A – Align across the enterprise, D – Develop others..
- OR for an individual contributor, they will be a subject matter expert within own discipline and will guide technical direction. They will lead collaborative, multi-year assignments and guide team members through structured assignments, identify the need for the inclusion of other areas of specialisation to complete assignments. They will train, guide and coach less experienced specialists and provide information affecting long term profits, organisational risks and strategic decisions..
- Advise key stakeholders, including functional leadership teams and senior management on functional and cross functional areas of impact and alignment.
- Manage and mitigate risks through assessment, in support of the control and governance agenda.
- Demonstrate leadership and accountability for managing risk and strengthening controls in relation to the work your team does.
- Demonstrate comprehensive understanding of the organisation functions to contribute to achieving the goals of the business.
- Collaborate with other areas of work, for business aligned support areas to keep up to speed with business activity and the business strategies.
- Create solutions based on sophisticated analytical thought comparing and selecting complex alternatives. In-depth analysis with interpretative thinking will be required to define problems and develop innovative solutions.
- Adopt and include the outcomes of extensive research in problem solving processes.
- Seek out, build and maintain trusting relationships and partnerships with internal and external stakeholders in order to accomplish key business objectives, using influencing and negotiating skills to achieve outcomes.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
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.
How we rate this
Senior AI Software Engineer at Barclays rates 19 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.
Little AI. AI is not part of the work.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- How do you decide that one model's output is better than another's for a given task?
- How do you think about the risk of an AI system in this kind of role failing silently?
Adapt your resume
- List these exact terms on your resume: Prompt Engineering, AI Agents, ML Ops, AI Evaluation, and AI Safety. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
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