Top Python Jobs in London

Backend Software Engineers at Palantir build scalable software solutions, collaborate across teams, and develop systems for data processing and storage, enhancing product capabilities.

Backend Software Engineers at Palantir build and maintain scalable backend services, develop APIs, optimize applications for performance, and collaborate across teams to shape user workflows.

The Forward Deployed Software Engineer at Palantir collaborates with customers to architect and build AI-driven solutions using large-scale data to address critical challenges.

The engineer will automate database deployment, maintain stability, manage migrations, and collaborate across teams to enhance database operations.

The Forward Deployed Reliability Engineer ensures the stability of workflows using Palantir software, troubleshoots issues, collaborates with teams, and implements process improvements.

The role involves maintaining and optimizing Palantir software systems, developing automated workflows, and collaborating on infrastructure challenges for government solutions.

Forward Deployed AI Engineers develop Gen AI solutions by building workflows, implementing strategies, and solving real-world problems at scale with clients.

Forward Deployed Software Engineers design solutions for customer challenges, involving architecture discussions, coding, and project execution, while ensuring user impacts are considered.

As a Backend Engineer, you'll enhance accounting integrations, improve workflows, expand global offerings, and build a scalable platform architecture.

Provide legal analysis and support for European structured finance and fund finance transactions. Review and summarise transaction documents, advise rating analysts and committees on legal risks, manage external counsel reviews, monitor legislation and case law, and contribute to drafting legal criteria and rating methodology commentary. Represent DBRS with market participants and support preparation of rating reports.

Build and maintain a centralized risk platform that unifies data and decision-making across identity, fraud, and compliance. Develop foundational backend services, enable product teams to ship safely at scale, and collaborate with risk and product stakeholders to reduce fraud and improve trust.

Lead execution research and transaction cost analysis to inform algorithm roadmap. Build and govern TCA frameworks, run market-microstructure research and A/B tests, develop pre- and post-trade models, translate findings into production features, and partner with Product, Trading, and Technology while mentoring junior researchers.

Lead DevOps Engineer on an agile team supporting low-latency electronic trading, data analytics and quant environments. Provide technical leadership, develop and review production code, manage CI/CD and release activities, automate tooling, monitor capacity, and deliver third-level production support while advocating firmwide engineering practices.

Perform quantitative and qualitative manager research and due diligence on relative value and macro hedge funds. Analyze portfolio fit, returns, risk attribution, and make recommendations to the investment committee. Support ongoing monitoring of approved managers, deliver written analysis, ad hoc projects, and help build tools to improve team efficiency.

Lead design and delivery of scalable GenAI platforms and services: build RAG pipelines and agents, model/version management, monitoring and drift mitigation, cloud-native microservices and deployment, testing and guardrails to reduce hallucinations, ensure compliance, and mentor engineering teams.

Lead counterparty credit risk controls, analytics, and transformation initiatives across derivatives, securities financing, and prime services. Monitor exposures, manage portfolio thresholds, perform investigations, strengthen governance, and develop automation and analytics (Python, SQL, Tableau, Alteryx, AI/LLM). Partner with Quantitative Research, Technology, Product, and Credit Officers to improve data, controls, and reporting for CCR and support regulatory and audit deliverables.

Lead design and deliver high-performance, low-latency trading services. Build secure, observable, resilient microservices, drive architecture, incident response, CI/CD, AI-assisted engineering adoption, and mentor engineers.

Lead SRE responsible for improving reliability, observability, and operability of customer-facing microservices. Build automation and tooling to reduce toil, define SLOs/SLIs/error budgets, implement resiliency/self-healing patterns, drive performance testing and capacity planning, partner across teams, and govern safe AI-assisted engineering practices.

Provide end-to-end application and infrastructure service delivery for front-office equities trading systems, maintain production stability, monitor environments, troubleshoot incidents, escalate and communicate issues, and support incident/problem/change management across on-premises and cloud systems.

Design, develop, and integrate Python-based risk and PnL systems for Rates trading. Build scalable data pipelines, implement risk metrics and PnL attribution, collaborate with quants, traders, and risk teams, and support front-, middle-, and back-office processing across rates and options products.

Lead design, development, testing, and operation of ultra-low-latency C++ trading and risk modules, integrating FPGA acceleration. Drive latency optimization, CI/CD, AI-assisted engineering adoption, automation, and cross-team collaboration to ensure reliability and performance.

Lead design, build, and operate high-performance Linux platforms for low-latency electronic trading. Perform deep performance engineering (kernel, CPU/NUMA, networking), write automation and tooling, architect deployment models (containerization, immutable infra), leverage Agentic AI, interface with vendors, mentor teams, and ensure governance, reliability, and reusable solutions across businesses.

Lead development of low-latency equities algorithmic trading strategies and execution platform. Build simulation and automated testing, analyze and tune models/signals, support production incidents, and create scalable real-time processing solutions.

Lead technical design, develop secure cloud-native applications, drive adoption of enterprise-authorized AI-assisted engineering, improve automation and operational stability, evaluate vendors, and promote engineering excellence across teams.

Support the business resiliency governance team by building and automating metrics, dashboards, and reporting. Improve data quality and controls, track BCP/testing outcomes and remediation, produce audit-ready evidence, and translate resiliency needs into clear data requirements and technical specifications.