AI Engineer

Role Overview

• Build and maintain data layers that support hybrid retrieval architectures combining vector, keyword, and structured search
• Design retrieval strategies to enable efficient search across large economic datasets and research content
• Develop and optimise embedding pipelines, indexing strategies, and ranking approaches for high-quality retrieval
• Implement evaluation frameworks to measure retrieval quality, relevance, and system performance
• Design structured metadata models that improve discoverability and machine interpretability of datasets
• Support ontology development and knowledge graph structures used by AI applications
• Ensure high data quality, lineage, and traceability across AI workflows
• Collaborate with data engineering and product teams to maintain consistent data standards and schema evolution
• Develop predictive models that analyse macroeconomic indicators such as GDP, inflation, and unemployment to support forecasting and economic analysis
• Build analytical tools that assist research workflows, enabling economists and analysts to generate insights more efficiently
• Integrate these tools with other AI-driven products and workflows, enabling seamless analysis and decision-making
• Support experimentation and evaluation of models to ensure reliability and practical value in real-world research contexts
• Design and implement scalable pipelines for AI and data workflows used in production environments
• Develop monitoring and observability capabilities to track system performance, model behaviour, and data quality
• Work closely with product, research, and engineering teams to translate real user needs into robust AI solutions

Requirements

• Master’s degree in computer science, Data Science, or equivalent fields (e.g. Machine Learning, Artificial Intelligence)
• Strong proficiency in Python and modern AI frameworks (e.g. Lang Chain, Lang Graph)
• Solid understanding of LLMs, embedding models, and retrieval-augmented generation (RAG) systems
• Experience with search systems, vector databases, and hybrid retrieval architectures
• Familiarity with data modelling, metadata systems, or knowledge graphs
• Experience building and deploying AI systems in production environment
• Ability to work effectively with real users and evolving product requirements

Tech Stack

• Python

Benefits

• Private medical insurance, inclusive of dental, vision, and hearing
• Life insurance
• Company pension scheme, with a strong employer contribution
• Gym discounts
• 25 days holiday per annum
• 2 Macrobond days to use per annum for volunteering