Top Python Developer Jobs in London

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.

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.

Leads development of secure, scalable data platforms supporting batch, streaming, ML, and LLM workloads. Designs distributed data systems using Spark, Ray, Kafka, Iceberg, and OpenSearch; productionizes model training, deployment, monitoring, and lifecycle management; and builds governed LLM solutions. Provides technical leadership, code review, incident response, vendor evaluation, responsible AI guidance, automation, and mentorship across engineering teams.

Design, develop, and maintain secure, scalable software solutions as a seasoned agile team member. Produce high-quality production code, architecture/design artifacts, data visualizations, and troubleshooting. Use CI/CD, resilient application patterns, enterprise AI-assisted development tools, and validate AI outputs. Contribute to engineering communities and improve code hygiene and system architecture.

Leads development of high-performance, latency-sensitive trading systems using Java and Python. Oversees architecture, coding, testing, APIs, integration strategies, observability, resilience, security, incident response, and operational readiness. Guides agile delivery through technical planning, code reviews, retrospectives, and mentoring. Establishes responsible use of AI-assisted engineering tools and validates outputs for correctness, performance, and security in a regulated financial environment.

Leads software engineering for a secure, scalable cloud data platform supporting credit risk technology. Responsibilities include designing and delivering Python solutions, reviewing production code, building CI/CD pipelines, improving application resiliency, standardizing SDLC tooling, automating remediation, and guiding responsible AI-assisted engineering practices. The role also evaluates vendors and leads cross-functional delivery initiatives involving AWS, Databricks, Spark, Terraform, lakehouse architecture, observability, security, and governance.

Leads software engineering for JPMorganChase’s wholesale credit risk technology team. Responsibilities include developing and reviewing secure Python code, guiding technical teams, designing scalable cloud-native systems, and establishing enterprise governance for AI-assisted engineering. The role sets toolchain architecture, CI/CD quality gates, automation standards, responsible AI controls, and validation requirements while serving as a firmwide software development lifecycle subject matter expert.

Lead development of secure, scalable identity and access management services for public cloud platforms. Responsibilities include architecture, system design, production software development, reliability improvement, automation, design reviews, cross-team collaboration, technical leadership, and mentoring. The role requires cloud-native engineering experience, IAM or entitlement governance expertise, proficiency in languages and infrastructure technologies, continuous delivery practices, and a strong focus on security, resilience, and developer experience.

Develop and support enterprise data platforms using Python, SQL Server, Oracle, ETL, and business intelligence technologies. Build greenfield data-centric solutions, create dimensional data models, optimize queries, support dashboards, and collaborate with Operations, Risk, Finance, and investment-engineering teams. The role also requires translating complex business requirements, participating in Agile delivery and code reviews, supporting CI/CD, and embracing AI-enabled development.

Develop scalable Python and Java solutions for generative AI and machine learning within Morgan Stanley’s trade surveillance analytics platform. Build agentic applications using LLMs, RAG, vector storage, MCP, and A2A patterns; integrate databases, UI frameworks, and DevOps practices. Collaborate with global Agile teams, translate business requirements, write comprehensive tests, optimize code and queries, and follow enterprise SDLC governance.

Develop and deliver full-stack or backend software across the complete development lifecycle. Responsibilities include hands-on Python programming, system integrations, solution design, workflow planning, process optimization, quality assurance, unit testing, and implementing customer requirements. The role involves working with AWS, databases, React or TypeScript, Terraform, and agile delivery practices while collaborating closely with the team and supporting major IT solutions.

Develop and deliver full-lifecycle software solutions for clients, including front-end and back-end development, integrations, workflow planning, process optimization, quality assurance, solution design, and implementation of customer requirements. The role involves hands-on Python and AWS development, collaboration with team members, database and testing work, agile delivery, and occasional travel to UK client sites.

Leads the design and operation of highly available, scalable, and observable production infrastructure. Defines SLOs, error budgets, and reliability targets; drives incident response, root-cause analysis, and postmortems; develops automation and deployment tooling; champions monitoring and observability; evaluates platform technologies; and mentors engineers. The role also applies secure AI-assisted engineering practices to improve incident triage, testing, and delivery workflows.

Leads the design, implementation, maintenance, and continuous improvement of resilient infrastructure automation for algorithmic trading. Provides Linux-based electronic trading platform expertise, partners with development and infrastructure teams, manages technical risk, and supports scalable systems. The role includes technical leadership, mentoring engineers and SREs, full-lifecycle ownership, incident review, and adoption of SRE practices. Advanced Python, Unix/Linux, infrastructure automation, debugging, CI, Git, Jenkins, and software engineering expertise are required.

Leads software engineering for an AI/ML data platform, designing, developing, testing, troubleshooting, and operating secure, scalable Python applications in containerized cloud-native environments. Partners with product and data teams, promotes responsible AI-assisted development, automates recurring remediation, evaluates technology solutions, and mentors junior engineers.

Develop and support secure, scalable software for AI/ML data platforms. Responsibilities include Python architecture and development, cloud-native and containerized application delivery, code review, testing, troubleshooting, operational stability, and automation of recurring remediation. The role also promotes validated AI-assisted engineering practices and collaborates with product managers and data strategy teams. Preferred experience includes graph databases such as AWS Neptune and generative AI engineering pipelines.

Develop and maintain reliable, testable Python systems supporting Cboe Europe's exchange trading operations. Responsibilities include designing new products and features, participating in R&D projects, providing production support and incident response, conducting post-mortems, and collaborating with business development, sales, and global software teams.

Designs, develops, and optimizes distributed computing solutions across HPC, Kubernetes, and cloud environments. Builds software in C++, Python, and Go; deploys applications using Kubernetes and HPC/grid technologies; and applies generative AI and observability tooling to improve monitoring and performance. Collaborates with cross-functional teams to deliver secure, scalable compute platforms.

Build and own backend platform capabilities enabling data scientists, machine learning engineers, and simulation engineers to create, train, and deploy physics-informed models. Collaborate cross-functionally with backend, frontend, design, data science, and simulation teams. Develop scalable, observable production software using Python and Go, including testing, containerization, CI/CD, authentication, event-driven messaging, and Kubernetes-based applications.

Develop and expand regulatory technology software using Python, translating business requirements into technical specifications and production code. Collaborate with project managers, business analysts, engineers, and non-technical stakeholders to deliver the product roadmap. Contribute to architecture, design reviews, testing practices, code analysis, refactoring, and platform performance, security, and maintainability. Build regulatory domain expertise and take ownership of parts of the product portfolio.

Build, maintain, and scale e-commerce backend services using Python and Django. Develop REST APIs and features for catalogs, inventory, carts, checkout, orders, payments, and customer accounts. Integrate external services, optimize databases and performance, implement security and access controls, write tested code, resolve production issues, and contribute to architecture, code reviews, deployment, and CI/CD.

Develop and maintain derivatives credit risk applications, optimize performance, and support CI/CD processes while collaborating with front office teams.

Build and optimize Python/FastAPI backend services for an AI infrastructure platform, integrating with PostgreSQL for reliable, high-performance data operations. Diagnose bottlenecks, improve system stability, make architecture decisions, and deliver features end to end from design through deployment. The role requires strong systems engineering fundamentals, testing, observability, scalability, and effective collaboration with technical leadership while using AI coding tools responsibly.