AI Platform Engineer

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.

Join Us as an AI Platform Engineer – Shape the Future of AI at Barclays. We’re excited to launch a groundbreaking initiative at Barclays - building a next-generation platform that empowers front-office developers (Quants and Strats) to create high-performance, AI-driven applications. As an AI Platform Engineer, you’ll play a pivotal role in designing, building, and scaling robust platform components that enable advanced AI/ML workloads across both on-premises and cloud environments. This is a hands-on engineering role where your expertise will directly influence how we deliver secure, scalable, and innovative solutions. You’ll collaborate with diverse teams, solve complex challenges, and help shape the technical direction of a platform that will transform how AI is leveraged in financial services. To be successful as an AI Platform Engineer at this level, you should have experience with: • Proven experience in Python engineering, with a focus on backend and infrastructure tooling. • Deep knowledge of AWS services (IAM, KMS, CloudFormation, API Gateway, S3, Lambda, ECS, Glue, Step Functions, MSK, EKS, Bedrock). • Experience scaling platforms for AI/ML workloads and integrating generative AI tooling. • Understanding of secure software development, cloud cost optimization, and platform observability. • Ability to communicate complex technical concepts clearly to technical and non-technical audiences. • Demonstrated capability to guide engineering teams and influence technical strategy. Some other highly valued skills may include:

• Experience with MLOps platforms such as Databricks or SageMaker, and familiarity with hybrid cloud strategies (Azure, on-prem Kubernetes). • Strong understanding of AI infrastructure for scalable model serving, distributed training, and GPU orchestration. • Expertise in Large Language Models (LLMs) and Small Language Models (SLMs), including fine-tuning and deployment for enterprise use cases. • Hands-on experience with Hugging Face libraries and tools for model training, evaluation, and deployment. • Knowledge of agentic frameworks (e.g., LangChain, AutoGen) and Model Context Protocol (MCP) for building autonomous AI workflows and interoperability. • Awareness of emerging trends in GenAI platforms, open-source MLOps, and cloud-native AI solutions

You may be assessed on the key critical skills relevant for success in role, such as risk and controls, change and transformation, business acumen strategic thinking and digital and technology, as well as job-specific technical skills. This role can be based out of our Glasgow or Canary Wharf office.