Top Python Developer Jobs in London

Build scalable software, data pipelines, analytical infrastructure, and research tools for investment teams. Translate quantitative models and research ideas into reliable production systems, collaborate with researchers, portfolio managers, traders, and engineers, and solve technically challenging data-intensive problems. The role requires strong Python and software engineering fundamentals, experience with complex datasets, communication skills, adaptability, and interest in financial markets.

Design, develop, test, deploy, and maintain Python applications, services, APIs, platforms, libraries, and tools supporting investment workflows including research, trading, risk management, data, and enterprise operations. Collaborate with investment professionals, quantitative researchers, and engineers; contribute to architecture and engineering best practices; and solve complex technical problems in a dynamic environment.

Develop secure, scalable backend and data solutions using Java, Python, Spring Boot, Databricks, Kafka, and cloud technologies. Responsibilities include designing microservices and event-driven architectures, integrating SQL and NoSQL databases, building data workflows, writing automated tests, reviewing code, troubleshooting production systems, and improving operational stability through automation. The role also contributes to agile practices, AI-assisted development, communities of practice, and enterprise software engineering standards.

Design, develop, deploy, and maintain advanced AI products and data pipelines. Collaborate with engineers, data scientists, and product owners to deliver production-grade, secure, scalable code. Architect AI-enabled engineering workflows, improve SDLC automation, ensure compliance, and provide technical leadership and architecture governance.

Designs, develops, tests, troubleshoots, and maintains secure, scalable software solutions within an agile Market Risk Technology team. Produces architecture and design artifacts, develops production code, analyzes large datasets, and improves system architecture, coding practices, resiliency, and automation. Uses enterprise-authorized AI-assisted development tools responsibly while validating generated code for correctness, performance, and security. Preferred experience includes Python, AWS, and data engineering.

Leads software engineering for JPMorganChase’s Market Risk Technology team, designing, developing, testing, and troubleshooting secure, scalable production systems. Responsibilities include code review, operational stability, automation, AI-assisted engineering adoption, responsible AI practices, vendor and architecture evaluations, and technical leadership. The role emphasizes Python, AWS cloud-native architecture, microservices, distributed systems, APIs, event-driven systems, data platforms, agile delivery, security, and financial services technology.

Lead design and delivery of real-time marking, pricing, and market data platforms for Rates Nonlinear. Build secure, high-quality production code, drive AI-assisted engineering adoption, collaborate with front office and quant teams, and lead cross-functional initiatives to ensure resilient, scalable solutions across the trade lifecycle.

Develop and maintain Python-based automated testing using Pytest, BDD frameworks, SQL validation, Kubernetes, and CI/CD pipelines. Test and troubleshoot applications in AWS, Azure, and containerized environments while contributing within Agile teams. The role also involves coaching and mentoring team members, collaborating with clients and colleagues, and delivering quality engineering solutions. This is a six-month hybrid contract in London requiring active SC clearance.

Leads hands-on development of secure, scalable cloud-native software, data engineering, backend systems, and AI/ML infrastructure. Designs microservices and distributed applications, builds production-scale data platforms, develops architecture artifacts, and promotes responsible AI-assisted engineering practices. Works with AWS data services, containers, Kubernetes, DevOps, and MLOps while supporting engineering standards, automation, troubleshooting, and stakeholder communication.

Build and deploy production-scale generative AI, data, and analytics solutions for FX sales and trading. Develop machine learning models, data pipelines, dashboards, and application features while ensuring data governance and need-to-know controls. Collaborate with traders, quants, sales, technology teams, and senior stakeholders to translate requirements into efficient designs. Provide technical leadership, production support, lifecycle improvements, and mentorship to junior engineers.

Develop production-scale generative AI, machine learning, data, and analytics solutions for FX sales and trading. The role involves building Python-based applications and pipelines, integrating data governance and access controls, collaborating with traders, quants, and stakeholders, supporting production systems, improving development practices, delivering large-scale projects, and mentoring junior engineers. Financial-market knowledge, modern Gen AI technologies, databases, messaging systems, and cloud-native development are valuable.

Build and integrate APIs, optimize lending platforms for performance and scale, and contribute to architectural decisions within the Python Infrastructure team. The role uses Python and FastAPI, with services deployed through Docker and Kubernetes on AWS and continuous delivery managed by ArgoCD. Responsibilities include developing modern Python applications, writing automated unit, integration, and functional tests, and collaborating with a highly engaged engineering team.

Build and improve high-throughput data infrastructure processing billions of market data points daily. Solve distributed-systems challenges, collaborate with quantitative researchers and traders, improve platform reliability, perform incident response and root-cause analysis, and contribute through code reviews and mentoring. The role uses Python and Java alongside Kafka, ArcticDB, Airflow, Spark, and database technologies at multi-petabyte scale.

Designs and develops scalable Python backend services, REST APIs, microservices, and AWS cloud applications supporting genomic healthcare and research. Responsibilities include database integration, identity and access management, test automation, troubleshooting, feature ownership, and collaboration with frontend, QA, platform, and external teams. The role also involves maintaining reliable infrastructure, contributing to technical specifications, and mentoring junior engineers.

Develop and deploy high-performance full-stack software for trader workflow tools within Citi’s Strategic Equity Solutions team. Responsibilities include designing microservices, collaborating with business stakeholders, translating trading requirements into technical solutions, writing clean code, mentoring engineers, evaluating AI tooling, and owning the complete software lifecycle through testing, deployment, monitoring, and production support.

Develop and maintain Python applications calculating counterparty credit risk and Basel capital metrics. Enhance CI/CD, testing, release management, performance optimization, profiling, documentation, and cloud workflows. Collaborate with Quant, Risk, Front Office Technology, and development teams to integrate model updates and technologies. Analyze complex application issues and serve as a subject matter expert for stakeholders.

Develop and maintain scalable Python data-processing systems for genomic and long-read sequencing workflows. Design resilient AWS services, distributed big-data systems, microservices, containerized solutions, and automated testing frameworks across cloud and on-premises infrastructure. Troubleshoot issues, collaborate in an agile environment, and assess emerging sequencing technologies supporting clinical genome research.

Build backend Python services, real-time data pipelines, TypeScript and React operator applications, and secure Azure infrastructure for distributed radar systems. Own production services, infrastructure as code, instrumentation, scalability, reliability, and security while collaborating with software, hardware, systems, and field teams. The role also involves influencing architecture, using AI coding tools thoughtfully, and quarterly travel to San Francisco.

Develop Python applications, quantitative tools, data pipelines, and cloud infrastructure supporting commodity trading and research across agriculture, metals, and energy. Build pricing, backtesting, risk, PnL, statistical modeling, and machine learning solutions; integrate alternative datasets; automate workflows; and maintain reliable research and trading systems while collaborating with researchers, traders, data engineers, and infrastructure specialists.

Lead the design, development, testing, and delivery of scientific and engineering software in Python. Translate technical methods into reliable, maintainable applications; make architectural decisions; establish testing, documentation, version control, CI, and release practices; verify reproducible calculations; and provide technical documentation, knowledge sharing, and a structured handover. The role also involves SQL, scientific or data-intensive software, collaboration with engineers and analysts, and contributing to related projects during a 3–6 month engagement.

Develop and support Python platforms for custom FICC index and benchmark solutions. Responsibilities include designing scalable software, collaborating with product and research teams, troubleshooting production and data issues, modernizing platforms through cloud adoption, improving testing and CI/CD, and supporting systems throughout the development lifecycle. The role requires strong software engineering, SQL, Linux, production support, quantitative technology, and financial services capabilities.

Develop and maintain Python applications for counterparty credit risk and Basel Capital calculations. Responsibilities include optimizing performance, supporting CI/CD and cloud workflows, expanding automated test suites, conducting profiling, documenting processes, and collaborating with Quant and Technology teams on model updates. The role also analyzes complex system issues and serves as a subject matter expert for stakeholders.

Lead backend software development for an automated electronic circuit board design platform. Collaborate with product, hardware, algorithms, and software teams to plan, build, test, and iterate on solutions. Work across data models, algorithms, pipelines, infrastructure, APIs, database queries, and machine learning models. Co-design, review, and pair with other senior developers while promoting high-quality agile engineering practices.

Build and continuously deliver scalable, resilient, highly available software products for clients. Responsibilities include feature development, CI/CD adoption, architecture and system design, production operations, monitoring, testing, performance optimization, mentoring engineers, and promoting engineering best practices. The role requires strong full-stack development capabilities across JavaScript/TypeScript, Python, and/or Go, cloud infrastructure expertise, effective communication, and a collaborative approach.

Develop and maintain the OpenTelemetry Python SDK and instrumentation libraries, focusing on generative AI agents, asynchronous workflows, performance, and runtime diagnostics. Collaborate with open-source maintainers, shape observability conventions, lead projects from design through release, mentor engineers, support technical direction, and help customers troubleshoot instrumentation issues.