Top Python Jobs in London

Design, develop, and deliver frontend (React) and backend services; produce architecture artifacts; analyze large data sets and visualizations; improve code quality and system resiliency; mentor junior engineers; use enterprise-authorized AI-assisted development tools; contribute to engineering communities and continuous improvement of infrastructure platform services.

Lead technical pre-sales for Datadog in the public sector: deliver demos and POVs, own trial engagements, qualify and technically close complex opportunities, present product briefings, record CRM feedback, and collaborate with sales and product teams while traveling up to 45%.

Integrate autonomy software onto unmanned aircraft, prepare flight-ready systems, support on-site flight tests, debug hardware/software issues, capture and analyze flight data, collaborate with autonomy/GNC/systems teams, and support certification and continuous improvement for mission deployments.

Lead Product Analyst for Europe & UK Regional Expansion driving KPI performance, ownership of analytics for product launches, forecasting, experimentation, and building reusable data assets. Partner with PMs, engineers, and analysts to influence product decisions and scale Wise products across markets.

Senior security researcher responsible for large-scale data collection and analysis, operating and building honeypots, performing vulnerability research and reverse engineering, developing automated tooling and GenAI/LLM workflows, collaborating with intelligence teams, reproducing vulnerabilities, and publishing technical research.

Design, build, and maintain AI agents and automated workflows for marketing. Identify automation opportunities, deploy and monitor agents, integrate with marketing tools, and report efficiency and business impact. Ensure data quality, privacy, and documentation, and enable marketing teams to adopt automations.

Lead product strategy for Fundamental Fixed Income (focus on Investment Grade credit), liaise between PMs and client-facing teams, support sales and thought leadership, produce pitches/RFPs/market commentary, defend and grow AUM, tailor product positioning, and supervise junior strategists while solving product and client issues across the firm.

Lead backend platform engineer to design, build, and maintain Java/Spring Boot libraries and frameworks for asynchronous, distributed microservice ecosystems. Drive standardisation, tooling, SDLC practices, security and compliance, mentor engineers, collaborate with SDLC/infrastructure teams, and govern enterprise AI-assisted engineering practices to improve delivery, quality, and automation.

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.

Assess and monitor client-level counterparty credit exposures, advise on complex deals, enhance exposure and margin methodologies, partner with Front Office, Credit, Technology, and Sales, and support regulatory, audit, and firm-wide risk projects.

Develop, test, and deploy software solutions for automated trading systems in partnership with Quantitative Researchers. Implement high-performance, scalable systems using advanced quantitative techniques, distributed computing, ML/NLP, and strong software engineering practices. Collaborate on priorities, deliver custom solutions, and engage with senior team members during an 11-week internship.

Conduct quantitative research and statistical analysis on crypto markets to develop, backtest, and implement automated trading strategies. Work with large and unconventional data sets to build valuation models, refine algorithms, and deploy signals in live trading to drive P&L growth.

As a Quantitative Research Analyst, you will develop and test automated trading strategies using statistical techniques and algorithms, conduct research, and analyze data.

Conduct research, statistical analyses, and develop automated trading strategies using large data sets and sophisticated statistical techniques.

FPGA Engineers at Citadel Securities design and deploy FPGA solutions to enhance trading systems, maximizing efficiency and performance.

The Site Reliability Engineer will provide support and diagnose issues within a real-time, distributed environment, focusing on large-scale application and infrastructure management, with basic required skills in UNIX/Linux, networking, SQL, and scripting languages.

As a Model Developer, you will deliver end-to-end model solutions using Python, collaborate with actuarial teams, mentor juniors, and improve model development practices.

Develop and maintain scalable cloud ecosystems using Golang and Python, enhancing backend microservices and collaborating within a fast-paced team.

Provide technical expertise to customers deploying and integrating Shield AI's Hivemind autonomy software. Develop autonomy applications, deploy AI infrastructure at customer sites, train and support customers, debug API integrations, collaborate with product/engineering, create documentation and training materials, and assist sales. Travel to customer sites (~30%).

Integrate and deploy autonomy software onto unmanned aircraft, prepare flight-ready systems, support on-site flight tests, debug hardware/software, capture and analyze flight data, collaborate with autonomy/GNC/test teams, and support certification and continuous improvement for reliable autonomous operations.

Lead simulation-driven testing and automation for Hivemind autonomy software: develop automated regression/integration/system tests, build simulation-based test frameworks (SIL/HIL/VIL), create Python tools for test automation and data analysis, integrate testing into CI/CD, and collaborate with engineering teams to diagnose and fix issues while maintaining test documentation and metrics.

Lead and develop a team of Forward Deployed Engineers to execute customer onboarding, on-site deployments, troubleshooting, and sustained adoption of the Hivemind SDK. Drive field feedback into product, translate mission goals into technical milestones, and partner with engineering and product teams to improve deployment readiness and customer outcomes.

Provide technical expertise to deploy and integrate Shield AI's Hivemind autonomy software at customer sites. Develop AI/autonomy applications using the Hivemind SDK, troubleshoot API/software integration, deliver technical training, create documentation and training materials, collaborate with product and engineering teams on customer feedback, support sales with technical queries, and travel to customer sites (~30%).

As an Applied AI Engineer, you will build AI applications for public sector clients, create and evaluate datasets, and collaborate with teams to address challenges using AI solutions.

Lead architecture and hands-on development of production-grade agentic AI platforms: runtime orchestration, governance, multi-agent coordination, model-agnostic integrations, API-first interfaces, monitoring, evaluation, and secure, multi-tenant deployments while mentoring engineers and producing architecture artifacts.