Top Python Jobs in London

Provides embedded technical consulting to strategic customers using the CrowdStrike Falcon platform. Responsibilities include Falcon deployment, configuration, troubleshooting, module adoption, integrations, vulnerability and asset management, threat hunting guidance, incident management support, scripting through Falcon APIs, project planning, and customer training. The role requires security platform experience, knowledge of Windows, macOS, and Linux, strong communication skills, and up to 20% travel.

Lead AI architecture and engineering for enterprise agentic AI systems. Define standards for RAG, agents, orchestration, evaluation, security, and governance; provide hands-on technical leadership, mentor engineers, and align cross-functional stakeholders to deliver secure, compliant AI solutions.

Build full-stack AI-enabled applications and backend services integrating MCP servers, LLMs, RAG retrieval, and agent orchestration. Design reusable MCP tools/skills, implement secure RBAC, ensure observability, and prepare deployments for OpenShift/Kubernetes while collaborating across product and platform 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.

Drive the end-to-end development of data products for Asset Management by translating business needs into requirements, coordinating data and technology teams, ensuring governance and quality standards, supporting adoption and value realization, and improving data product operating models. The role also evaluates existing products for duplication and consolidation opportunities while providing hands-on expertise across priority initiatives.

Operate and improve enterprise endpoint security, visibility, zero trust, and network access systems. Responsibilities include incident triage, anomaly investigation, policy tuning, vulnerability remediation, security documentation, cross-functional collaboration, automation with Python and SOAR platforms, and mentoring security engineers. The role supports security investigations and maintains resilient production security systems at enterprise scale.

Build high-performance quantitative trading infrastructure, including market-data, backtesting, simulation, model-serving, execution, and monitoring systems. Develop low-latency C++ services and scalable Python research pipelines, optimize throughput and latency, productionize machine-learning models, and partner with researchers and traders to deploy reliable live trading strategies.

Manage daily FX currency-overlay order flow, mitigate risk, and ensure accurate trade execution. Serve as a product subject-matter expert by designing currency risk-management solutions for institutional clients. Review procedures, data flows, and system dependencies to identify control gaps and improvements. Develop advanced analytics using statistical methods and large datasets to improve client solutions and generate business opportunities, collaborating with Trading, Sales, Technology, and Operations.

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.

Design and deliver enterprise-grade machine learning systems and AI-powered applications for banking. Build scalable, secure, distributed applications and automated cloud, desktop, and ML pipelines. Apply MLOps practices for versioning, reproducibility, and observability while collaborating with cloud and site reliability engineering teams. Develop reusable libraries and business-critical, data-intensive solutions, aligning machine learning problems with business objectives. The role may include mentoring or people leadership.

Trade refined oil products by managing client and broker flows, pricing and hedging transactions, developing fundamental and technical trading ideas, and managing complex risk. Responsibilities include marking forward curves, providing market commentary, hedging secondary exposures, sizing positions, supporting client engagement, and maximizing franchise revenue while maintaining strong controls and regulatory standards.

Leads architecture for JPMorgan Chase’s enterprise cloud platform across AWS, Azure, and GCP. Advises on workload placement, evaluates emerging cloud technologies, designs adoption tooling, and establishes architecture governance and platform guardrails. Develops and reviews production code, guides engineering teams, and promotes secure cloud-native practices. The role also governs AI-assisted and agentic architecture workflows, emphasizing human validation, data sensitivity, auditability, resiliency, and security.

Off-cycle quantitative research intern supporting systematic trading, financial engineering, statistical modeling, portfolio optimization, and derivatives pricing. Responsibilities include developing mathematical models and algorithms, valuing and hedging transactions, conducting alpha research, calibrating models, optimizing pricing, managing portfolio risk, and collaborating with traders, technologists, sales, and risk teams. Candidates gain hands-on global markets experience and may be considered for full-time employment after successful completion.

Embeds with Markets, Banking, and Payments teams to identify high-value generative AI opportunities. Translates business needs into technical requirements, reusable components, and production-grade solutions. Owns architecture and development across data, retrieval, prompting, orchestration, evaluation, deployment, and iteration. Partners with Technology and data science teams to meet enterprise resilience, controls, and risk standards while delivering measurable commercial impact.

Provide middle-office trade support for rates trading by capturing and validating trades, managing lifecycle events, investigating risk and profit-and-loss discrepancies, producing exposure reports, supporting regulatory controls, testing system changes, and improving processes. The role coordinates closely with trading, risk, finance, settlements, and collateral teams in a high-volume, time-sensitive environment.

Leads software engineering for global commodities trading desks, developing secure, scalable applications and resolving reporting issues. Provides technical direction, partners with Product and Financial Controllers, and serves as a subject matter expert. Drives responsible adoption of AI-assisted engineering, agentic development pipelines, automation, testing, security, resiliency, and SDLC governance. Requires strong Python expertise, front-office trading experience, risk and PnL reporting knowledge, cloud-native development, and independent problem-solving.

Develop and deploy statistical, machine learning, mathematical, and optimization models for Prime Finance. Responsibilities include forecasting borrow rates and demand, optimizing pricing and inventory allocation, researching alpha signals and hedging strategies, building analytics infrastructure, managing model risk, and communicating results to trading, technology, risk, and senior stakeholders. The role also mentors junior researchers and documents methodologies.

Build and maintain DevSecOps tooling for AWS cloud environments, including threat modeling, security guardrails, policy-as-code, vulnerability analysis, compliance reporting, and runtime security visibility. Develop automation for security findings and software supply chain controls, support audits and incident response, and provide remediation guidance to engineering teams. Collaborate with platform engineers, product squads, risk, and governance teams while using authorized AI-assisted development tools securely and validating generated outputs.

Leads a team building secure, production-grade AI-driven software systems. Responsibilities include software architecture, Java or Python development, AI/ML integration, LLM and generative AI applications, algorithm validation, automated testing, CI/CD, cloud-native development, troubleshooting, and operational reliability. The role also establishes responsible AI practices, validates AI-assisted engineering outputs, mentors engineers, translates business requirements into technical roadmaps, and ensures timely delivery through Agile methodologies.

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 liquidity reporting and regulatory change initiatives within Corporate Treasury Middle Office. Responsibilities include managing regulatory and audit deliverables, resolving reporting issues, improving controls and data quality, developing business requirements, testing data and reports, coordinating technology implementations, analyzing large datasets, and presenting findings to senior stakeholders and regulators. The role uses data and cloud technologies to modernize liquidity reporting and governance.

Develop and deliver production AI/ML solutions across the full lifecycle using Agile methodologies. Translate business requirements into technical specifications, build secure production code and algorithms, create architecture artifacts, analyze large datasets, develop visualizations, troubleshoot systems, and identify improvements. The role requires expertise in machine learning, Python, Spark, distributed computing, AI frameworks, agentic workflows, and AWS services, while contributing to engineering communities and emerging technology initiatives.

Develop and enhance high-performance portfolio construction and quantitative research technology. The role involves full software development lifecycle ownership, designing scalable systems, applying Python or Java expertise, collaborating with technologists and stakeholders, communicating development progress, and contributing to innovation and continuous improvement within a large financial-services engineering team.

Conduct quantitative research for systematic trading and financial markets. Develop mathematical models, algorithms, and infrastructure to price, hedge, and trade financial products. Perform alpha research, model calibration, portfolio optimization, and risk management while collaborating with traders, technologists, sales, marketing, and risk teams. Translate research into trading applications and communicate findings clearly. The program includes hands-on training and may lead to full-time employment.

Lead the design and development of production-grade agentic AI applications for Markets Operations. Build reusable AI architecture patterns, orchestration frameworks, context management, evaluation pipelines, guardrails, APIs, infrastructure, and monitoring. Partner with researchers, engineers, data scientists, and operations stakeholders to deliver secure, reliable, compliant AI solutions. Drive continuous improvement, document technical decisions, influence architecture, and mentor engineers.