AI Engineer / Machine Learning Engineer

hackajob is collaborating with Barclays to connect them with exceptional professionals for this role.

Join us as an AI Engineer for Barclays Private Bank and Wealth Management, where you will be part of a growing engineering function focused on delivering the bank’s strategic AI agenda. You will contribute to the development of Agentic AI solutions that enhance front-office productivity, improve client experiences, and support innovative business outcomes across the organisation.

This is an exciting opportunity for an early-career engineer with a passion for AI and emerging technologies and strong software engineering fundamentals and a willingness to learn. The role will include developing AI-powered applications and services using modern Python-based frameworks, supporting the implementation of Generative AI and Agentic AI solutions, and collaborating with engineering teams to build scalable, secure, and production-ready applications that deliver business value.

To be successful as an AI Engineer, you should have:

• Strong proficiency in Python with hands-on experience in AI/ML libraries (LangChain, LlamaIndex, or similar) and building production-grade applications.
• Proven ability to design, test, and optimise prompts for Anthropic models, including implementing RAG (Retrieval-Augmented Generation) patterns, MCP, and A2A protocols
• Familiarity with ML model deployment pipelines, monitoring, versioning, and automated testing frameworks for AI applications

Some other highly valued skills may include (3 desirable skills):

• Experience with vector stores (Pinecone, Weaviate, or AWS OpenSearch) and semantic search implementations for context-aware AI applications
• Experience building RESTful or GraphQL APIs and designing scalable, event-driven architectures for AI-powered services
• Experience deploying and managing applications on AWS, including Amazon Bedrock, Lambda, API Gateway, and related services for scalable GenAI solutions

You may be assessed on the key critical skills relevant for success in the role, such as risk and controls, change and transformation, business acumen, strategic thinking, and digital and technology capabilities, as well as job‑specific technical skills.

This role will be based in Glasgow.

Purpose of the role

To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.

Accountabilities

• Identification, collection, extraction of data from various sources, including internal and external sources.
• Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
• Development and maintenance of efficient data pipelines for automated data acquisition and processing.
• Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
• Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
• Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.