Senior Tech Lead, Quantitative Analytics Engineering

ABOUT LSEG: LSEG (London Stock Exchange Group) is more than a diversified global financial markets infrastructure and data business. We are dedicated, open‑access partners with a dedication to excellence in delivering the services our customers expect from us. With extensive experience, deep knowledge and worldwide presence across financial markets, we enable businesses and economies around the world to fund innovation, manage risk and create jobs. It’s how we’ve contributed to supporting the financial stability and growth of communities and economies globally for more than 300 years.

Role Summary: The successful candidate will be responsible for leading the development and delivery of advanced Private Markets Analytics solutions, while driving the adoption of AI-powered capabilities to enhance product functionality, engineering productivity, and client value. This role requires hands‑on technical leadership across software engineering, system design, AI/LLM engineering, agile delivery and cloud‑native architectures, while managing a team of engineers and external partners. You will collaborate closely with Analytics Business, Product, Architecture and Research teams to deliver innovative Private Markets Analytics solutions aligned with LSEG’s strategic partnership with Microsoft and its cloud‑first vision and will play a key role in evolving the Private Markets Analytics platform and product suite through modern software engineering, scalable architecture and the integration of AI‑assisted capabilities, automation and intelligent decision‑support solutions for private capital markets.

What You’ll Be Doing:

• Lead the design, development and delivery of Private Markets Analytics product solutions, ensuring scalability, performance, maintainability, resilience and high engineering quality.
• Lead technical architecture and system design for distributed, cloud‑native applications and services.
• Drive adoption of AI/LLM technologies across Private Markets products, including prompt engineering, Retrieval-Augmented Generation (RAG), AI‑assisted workflows and intelligent automation where they deliver measurable business value.
• Lead and develop a team of engineers, fostering a strong engineering culture focused on innovation, delivery, quality and continuous learning.
• Own the engineering roadmap, aligning technical priorities with business objectives and Microsoft partnership initiatives.
• Deliver high‑quality analytics solutions to clients in collaboration with Product, Research, Architecture and Sales teams.
• Architect and implement cloud‑native solutions leveraging platforms such as Azure, Databricks and Snowflake.
• Extend and support a multi‑cloud and hybrid cloud platform for analytics workloads.
• Drive agile engineering practices, including CI/CD, DevSecOps, MLOps/LLMOps, automated testing and engineering best practices.
• Collaborate with multi‑functional teams to integrate AI agents, automation capabilities and modern AI services into business workflows.
• Ensure best practices in software architecture, engineering governance, AI governance, security, scalability, regulatory compliance and responsible AI.
• Provide technical leadership on architecture decisions, system design, technology selection and engineering standards across multiple initiatives.
• Mentor and develop engineers in engineering, system design, AI/ML technologies and modern development practices.
• Evaluate emerging technologies and recommend adoption where they improve product capability, engineering efficiency or client experience.
• Foster a culture of innovation, experimentation, engineering excellence and continuous improvement.

What You’ll Bring:

• Strong experience leading software engineering teams delivering enterprise‑scale Analytics, Private Markets or financial software solutions.
• Strong software architecture and system design skills with the ability to design scalable, resilient, distributed applications.
• Proven experience building and delivering API‑driven, cloud‑native, distributed systems.
• Hands‑on experience with Azure and modern cloud‑native application architectures.
• Experience with Databricks, Snowflake or similar enterprise data platforms.
• Strong understanding of software engineering best practices, including CI/CD, DevSecOps, automated testing, observability and secure software development.
• Strong programming skills in Python, with familiarity in C++, C#, or similar languages.
• Experience with AI/ML technologies and hands‑on knowledge of Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), AI agents, prompt engineering or similar generative AI technologies is highly desirable.
• Familiarity with AI orchestration frameworks (e.g. LangChain, Semantic Kernel, AutoGen or similar) would be advantageous.
• Knowledge of Private Markets, alternative assets, portfolio analytics, financial data platforms, Fixed Income or Multi‑Asset Analytics is a strong plus.
• Strong understanding of software architecture, scalability, performance optimisation and modern system design principles.
• Excellent communication, stakeholder management and technical leadership skills.

Equal Opportunities: We are proud to be an equal opportunities employer. We do not discriminate on the basis of anyone’s race, religion, colour, national origin, gender, sexual orientation, gender identity, gender expression, age, marital status, veteran status, pregnancy or disability, or any other basis protected under applicable law. Conforming with applicable law, we can reasonably accommodate applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs.