To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues.
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.
Embark on a transformative journey as a AI Engineer At Barclays, our vision is clear –To design, develop and improve software, utilising various engineering methodologies, that provides business, platform, and technology capabilities for our customers and colleagues. The location of your role is London.
Some other highly valued skills may include: * Experience building evaluation frameworks for agentic systems including agent benchmarking, reasoning traces, and monitoring observability for multi-step AI workflows in production. * Experience in vector databases, knowledge graphs, semantic search, and memory systems for stateful agents with understanding of retrieval optimisation and context management. * Good technical leadership with experience establishing platform standards, driving architectural decisions, and enabling teams through APIs, SDKs, documentation, and training. * Knowledge of responsible AI practices, model governance, security considerations for autonomous systems, and regulatory requirements in financial services or regulated environments.
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.
To be successful as an AI Engineer, you should have experience with: * Advanced experience in AI/ML platform architecture with confirmed designing and building scalable ML infrastructure, model serving platforms, and end-to-end MLOps systems at enterprise scale. * Experience developing agentic AI systems and LLM applications including multi-agent orchestration, tool use, planning frameworks, and production deployment of multi-layered AI workflows at scale. * Good technical knowledge of LLM fine-tuning, prompt engineering, RAG architectures, and modern frameworks (LangChain, LangGraph, LlamaIndex) with validated ability to architect and optimise agent-based solutions. * Experienced software engineering skills with proficiency in Python, distributed systems, microservices, cloud platforms (AWS/Azure/GCP), and GPU infrastructure with focus on building self-service AI platforms.
