Senior Tech Lead of Quantitative Analytics Engineering

Join LSEG as a Senior Tech Lead of Quantitative Analytics Engineering, focusing on AI and Large Language Models (LLMs). Lead a high-performing team of engineers, driving the design, development, and delivery of next-generation analytics and AI-powered solutions. Collaborate closely with various teams to deliver innovative solutions aligned with LSEG's strategic partnership with Microsoft.

• Lead a high-performing team of quantitative analytics and AI engineers in the design, development, and delivery of next-generation Analytics and AI-powered solutions.
• Drive the adoption of AI/LLM technologies across Analytics products, including prompt engineering, fine-tuning, RAG (Retrieval-Augmented Generation), and model evaluation.
• Architect and implement cloud-native solutions leveraging platforms such as Azure, Databricks, and Snowflake, and ensure best practices in model governance, risk, explainability, and compliance.
• Experience with Databricks, Snowflake, or similar data platforms
• Hands-on experience with cloud platforms (Azure preferred) and modern data/AI ecosystems
• Solid experience leading engineering teams, ideally within AI/ML or data platforms
• Strong programming skills in Python, and familiarity with C++, C#, or similar languages
• Familiarity with AI agents, orchestration frameworks (e.g., LangChain, Semantic Kernel, AutoGen, etc.)
• Strong experience in LLM/AI engineering, including hands-on work with large language models
• Strong understanding of software architecture, scalability, and system design
• Strong experience with agile software development methodologies and leading agile teams
• Proven experience building LLM-based applications, including RAG pipelines, agents, embeddings, and vector databases
• Degree (Master’s or equivalent) in Computer Science, Engineering, Mathematics, or related field
• ~10+ years of experience in technology, AI, or financial services
• Domain knowledge in financial markets (Fixed Income, Multi-Asset analytics) is a strong plus
• Experience working with large-scale data systems and pipelines
• Excellent communication and stakeholder management skills
• Experience with MLOps/LLMOps, model lifecycle management, and production deployment of AI systems
• Strong experience designing and delivering API-driven, distributed, cloud-native systems