AI Platform Engineer

Barclays Bank PLC
Glasgow, United Kingdom
2 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Compensation
£ 68K

Job location

Glasgow, United Kingdom

Tech stack

Artificial Intelligence
Amazon Web Services (AWS)
Amazon Web Services (AWS)
Unit Testing
Azure
Cloud Computing
Software Quality
Code Review
Identity and Access Management
Python
Open Source Technology
Secure Coding
Software Engineering
Software Requirements Analysis
Software Systems
Systems Integration
Large Language Models
Backend
Cloudformation
Kubernetes
HuggingFace
Machine Learning Operations
Functional Programming
Api Gateway
Databricks
Programming Languages

Job description

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 design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues., * 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.

Requirements

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.

About the company

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.

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