Top Tech Jobs & Startup Jobs in London

Develop and productionize machine learning models and AI agents for financial-market intelligence and client workflows. Responsibilities include forecasting, sentiment analysis, market classification, LLM/RAG agent development, backtesting, hallucination testing, governance, human-review controls, provider benchmarking, regulatory compliance, and cross-functional collaboration. The role also provides technical leadership and mentorship while applying advances in AI and machine learning to financial markets.

Work with Risk Management to gather requirements and develop/enhance risk systems. Build data analysis processes, valuations, and custom measures; create dashboards and reports; integrate systems with trading and middle-office; manage reference data; document processes, implement source control and deployment best practices, and evaluate new technologies.

Build and maintain market, economic, research, news, and internal data pipelines for AI and quantitative models. Design scalable data architectures, implement data quality controls, manage metadata and lineage, create APIs and model-ready datasets, and optimize pipeline performance. Collaborate with data scientists and analysts while ensuring data security, privacy, permissions, and reliable integration across tools and models.

Lead cloud security engineering across AWS/Azure/GCP: manage CSPM/CNAPP platforms, implement policy-as-code and IaC controls, resolve complex cloud security issues, mentor juniors, define requirements, and champion ITIL change/incident/problem processes.

Develop and integrate pricing models within a resilient, real-time event-driven framework. Contribute to quantitative libraries, implement data-driven development (unit tests, mocking, back-testing), collaborate with quants, data scientists, and engineers, research innovative solutions, and ensure conduct risk awareness while working with global teams.

Design, develop, and maintain matching engines, FIX gateways, and low-latency trading applications using Java and C++. Implement efficient in-memory data structures, optimize networking and concurrency, troubleshoot production issues, and collaborate with trading, product, and infrastructure teams across the full software development lifecycle.