Top Python Developer Jobs in London

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.

Lead design and implement IAM-focused public cloud platform services. Develop and maintain production code, drive architecture and reliability, automate remediation, lead reviews, mentor engineers, and collaborate across platform and trust teams to deliver secure, scalable cloud services.

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.

Join Markets Technology Trading as a Software Engineer II to design, develop, and troubleshoot secure, stable, high-quality Python code. Leverage enterprise AI-assisted development tools, collaborate in an Agile team, handle data processing and production engineering tasks, and apply SDLC practices to build performant, resilient applications while learning domain systems and secure coding standards.

Develop and maintain data pipelines and business applications to support model risk governance. Implement model performance monitoring, workflow automation, and LLM-enabled solutions using Python and web frameworks. Emphasize data controls, testing, AI-assisted development tooling, and collaboration with cross-functional stakeholders to deliver secure, reliable analytics and efficiency tools.

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.

Develops, tests, troubleshoots, and maintains secure, scalable software components within an agile engineering team. Responsibilities include writing Python code, analyzing data, supporting system design, applying SDLC practices, improving automation with authorized AI coding tools, and considering upstream and downstream system impacts. The role requires software development experience, database querying knowledge, testing, operational stability, CI/CD, application resiliency, and secure coding practices.

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 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.

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.

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.

Design, implement, and deliver full-stack features for the Validus Horizon platform. Build and maintain ETL/data pipelines and integrations, own small-to-medium projects, improve system performance and scalability, collaborate with stakeholders and clients, mentor team members, and present technical solutions and roadmaps to drive product and client success.

Develop quantitative foundations for a risk and PnL management platform supporting trading across asset classes. Build risk models, scenarios, performance attribution, pricing integrations, and scalable analytics infrastructure. Collaborate with traders, quantitative researchers, pricing quants, and technology teams to translate requirements into production systems for real-time risk and performance management.

Build and maintain backend services and APIs for a fintech platform using modern Python tools. Design scalable, secure systems, integrate third-party services, implement async and event-driven workflows, investigate distributed system issues, contribute to architecture and code quality, and mentor peers in a collaborative product team.

Design, build, and operate Python backend services, data processing pipelines, and internal web applications. Integrate platforms with Microsoft ecosystem, deploy containerized cloud-native apps, improve reliability and observability, support CI/CD, and collaborate with cross-functional teams to deliver data-driven forecasting and analytics solutions.

The role involves developing and maintaining Python micro-services for a proprietary trading platform, collaborating with traders and global teams, and integrating with analytics libraries.

Design, build, test, and maintain scalable full-stack web applications and integrations using Java, Python, and React. Implement AI-enabled features, event-driven data pipelines, and marketing integrations (CDP/CRM/CMS). Improve code quality via AI-assisted tools, CI/CD, observability, and security/compliance best practices while collaborating with product, marketing, and partners.

Lead design, development, and delivery of risk, pricing, trade capture, and commodities operations software. Collaborate with trading, quant, sales, and middle office to produce secure, high-quality production code, provide technical guidance, and drive product and architecture decisions. Promote cross-team collaboration, firmwide engineering practices, and mentor engineers to deliver scalable solutions.

Develop and scale Python-based APIs, web services, mobile and voice-assistant integrations, and internal editorial systems supporting high-traffic digital products. The role involves writing clean, tested code; collaborating through reviews and paired programming; working with databases and ORM frameworks; applying RESTful and software engineering principles; and contributing to continuous integration. Experience with modern Python frameworks, GraphQL, asyncio, Docker, AWS, Kubernetes, and search platforms is advantageous.

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.

Build and improve research and production infrastructure for quantitative trading. Develop Python and C++ systems, libraries, backend services, and workflow tooling for strategy research, testing, and deployment. Improve performance, algorithmic efficiency, scalability, and distributed compute capabilities while partnering with quantitative researchers and traders. Own projects through design, implementation, testing, rollout, and ongoing enhancement.