Senior Tech Lead, Quantitative Analytics Engineering

In this Tech Lead role, you will steer a high-performance team that builds next-generation Analytics and AI-powered solutions, with a focus on LLMs. You will blend AI/ML engineering with cloud-native platforms to deliver scalable analytics products for LSEG's global clients. You’ll work closely with Analytics, Product, and Research teams to align with Microsoft partnership initiatives and cloud-first goals. You drive LLM-enabled analytics, automation, and decision-support tools that impact financial markets. This is an opportunity to shape innovative AI-driven financial analytics at scale.

• healthcare
• retirement planning
• paid volunteering days
• wellbeing initiatives

• Lead design, development, and deployment of LLM-powered analytics solutions (agent-based systems, copilots, AI-driven workflows)
• Drive adoption of AI/LLM tech across analytics products (prompt engineering, fine-tuning, RAG, model evaluation)
• Lead and mentor a team of engineers, fostering innovation and continuous learning
• Own the LLM engineering roadmap aligned with business priorities and Microsoft partnership
• Deliver analytics and AI product solutions with Product, Research, and Sales teams
• Architect cloud-native solutions on Azure, Databricks, Snowflake
• Design scalable data pipelines and AI workflows for structured/unstructured financial data
• Develop API-first, SaaS/PaaS AI products (analytics, risk models, reporting)
• Extend and support multi-cloud/hybrid cloud for AI/Analytics workloads
• Advocate Agile practices, including CI/CD, MLOps/LLMOps, DevOps for AI systems
• Collaborate with cross-functional teams to integrate AI agents into business workflows
• Ensure model governance, risk, explainability, and compliance in financial services
• Mentor engineers in AI/ML, LLM tech, and modern software practices
• Foster a culture of innovation and continuous improvement

• LLM/AI engineering hands-on experience
• Proven track record building LLM-based apps, RAG pipelines, agents, embeddings, vector databases
• Experience leading engineering teams in AI/ML or data platforms
• Agile software development leadership
• Cloud platforms experience (Azure preferred) and modern data/AI ecosystems
• Experience with Databricks, Snowflake or similar
• Familiarity with AI agents and orchestration frameworks (LangChain, Semantic Kernel, AutoGen)
• API-driven, distributed, cloud-native system design
• MLOps/LLMOps, model lifecycle management, production AI deployment
• Strong Python; familiarity with C++, C# or similar languages
• Experience with large-scale data systems and pipelines
• Domain knowledge in financial markets (Fixed Income, Multi-Asset analytics)
• Strong software architecture, scalability, and systems design
• Excellent communication and stakeholder management
• Master in Computer Science (or related) and ~10+ years tech/AI/finance experience

• communication
• stakeholder management
• collaboration
• Python
• Azure
• Databricks