Top Tech Jobs & Startup Jobs in London

Lead design and development of low-latency, event-sourced microservices for algorithmic trading. Hands-on coding (primarily Java or Rust), performance tuning, market-data handling (KDB), integration, mentoring, and architectural leadership to enable low-latency eTrading platforms and related simulation/replay utilities.

Design, build, test, and maintain backend Java/Spring services and microservices that integrate with blockchain networks. Implement node connectivity, transaction submission, on-chain event monitoring, wallet interactions, and smart contract deployment. Support async/event-driven processing, production debugging, code reviews, documentation, and Agile delivery while following security and quality standards for enterprise-grade digital asset platforms.

Design and develop high-performance frontend applications for global electronic trading and algorithmic trading platforms. Build real-time data visualizations, handle streaming market data, optimize low-latency UI performance, and support distributed applications. Provide technical oversight, follow application development and governance standards, and collaborate with technology and product teams to deliver compliant, scalable solutions.

Drive software vulnerability remediation across application portfolios by enabling SAST and SCA fixes, dependency upgrades, containerization, and same-day releases. Review remediation plans, guide engineering teams through secure coding and pipeline improvements, coordinate contractor squads, review code submissions, promote security tooling, and track remediation metrics. The role also escalates technical blockers, validates testing and deployment evidence, and supports audit and compliance requirements.

Develop and enhance Citi’s digital assets platform as a backend Java engineer. Build enterprise-grade web applications leveraging blockchain and web3 technologies, apply scalable design patterns, support solution engineering, test and document software, resolve issues, and collaborate with distributed teams. Preferred experience includes Web3J, Web3JS, Solidity, DevOps, containerized applications, Agile/Scrum, and financial services.

Leads legal support for Citi’s EMEA investment bank lending, restructuring, and workouts businesses. Provides senior advice on complex syndicated, leveraged, acquisition, and private credit transactions; manages cross-border legal issues; advises on regulatory developments, risk, governance, and creditor rights; and serves as the senior escalation point for lending matters. The role also leads and develops a regional legal team and contributes to strategic planning and business initiatives.

Lead the architecture and development of scalable, secure, accessible frontend and fullstack web applications. Establish UI engineering standards, reusable component libraries, design system adherence, API and backend integrations, testing, performance, CI/CD, and security practices. Collaborate with product, UX, backend, infrastructure, and security teams to deliver complex technology initiatives. Provide technical leadership, mentor engineers, resolve complex system challenges, and ensure compliance with enterprise architecture and risk controls.

Build and deploy production-grade agentic AI systems for Citi business units. Develop Python-based agent reasoning, memory, delegation workflows, MCP servers, enterprise integrations, resilient error handling, guardrails, evaluation harnesses, and CI/CD pipelines. Collaborate with engineers and stakeholders, coach junior developers, conduct code reviews, and ensure secure, compliant, reliable AI deployments.

Lead the architecture and development of Citi’s global quantitative pricing platform. Build hybrid-cloud, high-performance computing infrastructure that distributes pricing models across large-scale grids, orchestrates jobs, optimizes resources, manages failures, and transfers high-volume market and trade data. Develop ML-powered monitoring and anomaly detection, and collaborate with front-office quants to deploy and optimize C++ and Python models for large-scale risk, P&L, derivatives, and XVA calculations.

Design and build massive-scale risk analytics platforms for market risk data. Responsibilities include architecting Spark data pipelines processing billions of trade-level calculations, developing intelligent APIs, integrating NLP-based data exploration, modeling datasets in OLAP engines such as Pinot, Druid, and Trino, and creating analytical dashboards. The role partners with front-office, quantitative, and risk stakeholders while leading complex technical projects involving financial risk calculations, derivatives, VaR, and FRTB.