Top Java Developer Jobs in London

Own technical roadmaps and large-scale backend projects for Wise’s global KYC and onboarding systems. Design scalable Java microservices, clean APIs, asynchronous integrations, and risk-mitigation systems supporting regulatory compliance. Address technical debt, reliability, scalability, security, and data management while solving ambiguous problems and leading cross-team delivery. Mentor engineers, promote code quality, and improve verification automation and customer experiences.

As a Senior Software Engineer II, you will drive the technical vision for backend solutions, enhance recipient management, and ensure system reliability.

Build and improve fraud prevention and account integrity systems protecting customers from account takeovers and financial crime. Develop backend services and frontend features, design and operate CI/CD pipelines, and work with distributed and concurrent systems. Optimize relational and non-relational databases, apply test-driven development, and own projects end to end with a customer-focused, data-driven mindset. Collaborate with Product, Data Science, and Investigations teams; machine learning lifecycle experience is beneficial.

Lead and mentor an agile team to design, develop, secure, and operate scalable cloud-native applications using modern front-end tech and AI-assisted engineering practices; drive automation, code quality, resiliency, and operational stability.

Lead development of equities algorithmic trading strategies and execution platform. Build simulation and automated testing, analyze and improve strategy performance, troubleshoot production issues, and develop scalable real-time processing and automation to improve operational stability.

Lead design, development, testing, release, and production support for Equity Derivatives workflows. Own production outcomes, incident triage, stakeholder communication, UAT, architecture and observability. Drive adoption of AI-assisted engineering practices, maintain release discipline, gather telemetry for stability metrics, and improve system reliability and coding hygiene through cross-functional collaboration.

Lead technical design and development of AI-native systems for credit pre-trade markets. Build scalable AI platforms, modernize legacy systems, deliver secure production code, partner with trading and product teams, support production operations, evaluate vendors, and drive engineering best practices and communities of practice.

Lead backend engineering work using JVM languages to design scalable, reliable, secure, cloud-native, multi-cloud solutions. Drive domain modeling, performance optimization, zero-downtime releases, incident resolution, and operational excellence. Champion adoption and governance of enterprise-authorized AI-assisted engineering practices and SDLC toolchain automation while coaching teams on responsible, secure AI use.

Lead backend engineering efforts to design, build, and operate scalable, reliable, and secure cloud-native services using JVM languages. Drive domain modeling, performance optimization, zero-downtime releases, incident remediation, automated testing, and adoption of approved AI-assisted engineering practices while mentoring teammates and promoting reusable patterns.

Lead development of the QES trading platform: design, build, test, and maintain production-grade software. Collaborate with front office (trading, structuring, research), deliver secure high-quality code (Python/Java/TypeScript/React), automate operational remediation, and lead agile engineering practices and communities of practice.

Lead design and deliver scalable OMS and equities software using Java 17+. Build and maintain front-end UIs with JavaScript and modern frameworks (React/Angular). Drive adoption and governance of enterprise AI-assisted engineering practices, troubleshoot complex distributed/multithreaded systems, participate in code reviews and deployments, and collaborate across teams to ensure secure, high-quality production code.

Lead design and delivery of high-performance Java back-end systems for OMS/Sales. Provide technical direction, write and review secure production code, drive adoption and governance of AI-assisted engineering practices, ensure cloud-native (AWS/Terraform) scalability and operational stability, and promote SDLC best practices across teams.

Lead development of low-latency equities algorithmic trading strategies and execution platform. Build simulation and automated testing, analyze and tune models/signals, support production incidents, and create scalable real-time processing solutions.

Hands-on lead engineer responsible for designing, developing, reviewing, and shipping secure, production-ready payment systems. Drive architecture, operational stability, automation, vendor evaluations, and mentor engineers while contributing to technical direction and team culture.

Design, build, and maintain large-scale, secure data engineering solutions. Lead architecture, deliver production code, drive automation and operational stability, mentor teams, and evaluate vendor/technology choices to advance risk technology platforms.

Design, build, and maintain scalable, secure, cloud-native backend systems using JVM languages. Ensure reliability, performance, and zero-downtime releases; use domain modeling, automated testing, and enterprise AI-assisted tools to improve code quality and delivery.

Lead and deliver secure, scalable post-trade software solutions. Design, develop, review, and troubleshoot production code; drive architecture evaluations; automate remediation; promote CI/CD, resiliency, and cloud-native practices; mentor engineering communities and collaborate with vendors and internal teams.

Lead design, build, and operate cloud-native AWS microservices using Kubernetes. Drive CI/CD, containers, IaC, monitoring, reliability, and incident resolution. Champion AI-assisted engineering practices, mentor engineers, participate in architecture reviews, and optimize platform availability and scalability for low-latency trading.

Lead engineering on design, development, and operational stability of market-facing systems. Deliver secure, high-quality Java code, promote enterprise AI-assisted engineering practices, drive automation and resiliency, evaluate vendor solutions, and mentor teams while ensuring secure, compliant adoption of AI and cloud-native architectures.

Lead design and deliver high-performance, low-latency trading services. Build secure, observable, resilient microservices, drive architecture, incident response, CI/CD, AI-assisted engineering adoption, and mentor engineers.

Lead development of Java/Spring Boot microservices for J.P. Morgan Personal Investing. Design and evolve cloud-native, event-driven architectures on Kubernetes using Kafka, deliver features from estimation to production, write tests, participate in code reviews, maintain monitoring/alerting, and drive adoption of enterprise-authorized AI-assisted engineering practices and SDLC automation.

Lead engineering efforts for the Equity Derivatives trading platform: design, build, and troubleshoot Java/JVM microservices, adopt AI-assisted engineering practices, collaborate with traders, quants, product and production teams, and drive CI/CD, resiliency, and secure development across the Agile delivery lifecycle.

Join the Continuous Delivery team to design, build, and operate Wise's CD platform. Extend and evolve Spinnaker, create reliable deployment guardrails, improve shared platform foundations, use telemetry to reduce friction, and partner with engineering teams to adopt scalable deployment patterns and platform capabilities.

Lead development of Java-based services and front-end desktop apps to support pricing, quoting and market workflows for equities derivatives. Drive automation, integrate AI/ML autopricers, build scalable cloud deployments, design secure APIs, promote AI-assisted engineering practices, participate in code reviews, and collaborate across global teams.

Lead technical contributor on the ETF Technology team delivering secure, scalable Java/Oracle applications. Design, develop, test, and support production systems; partner with product, portfolio management, and platform teams; drive operational stability, automation, and adoption of enterprise AI-assisted engineering practices.