Top Python Jobs in London

The Platform Engineer will develop internal platform capabilities to enhance engineering team efficiency while ensuring security, reliability, and operational control, focusing on automation and user experience.

Leads revenue performance analysis, forecasting, budgeting, business modeling, and automated reporting. Investigates revenue drivers, challenges commercial assumptions, pressure-tests global P&L forecasts, and translates complex financial and commercial data into recommendations for senior stakeholders. Builds reporting solutions using data warehouse and billing data to support commercial decision-making.

Support the governance, development, validation, and improvement of Bupa’s ReMetrica-based Economic Capital Model. Responsibilities include economic capital assessment, regulatory reporting to executives, the Board, and the PRA, stress and scenario testing, risk calibration, model documentation, data quality controls, sensitivity analysis, and Solvency II compliance. The role also supports capital optimisation, reinsurance analysis, business decision-making, and continuous improvement initiatives while collaborating with actuarial, finance, and risk teams.

Leads global longevity reinsurance pricing referrals and business acceptance reviews. Evaluates best estimates, pricing models, deal structures, and expert judgments while coordinating with global and local pricing teams. Supports assumption governance, methodology implementation, cross-reviews, and referral community engagement. Participates in client meetings, due diligence, and negotiations, while sharing best practices and guiding complex transactions across international markets.

Build and deploy production AI applications using Claude models within enterprise customer environments. Develop MCP servers, sub-agents, and agent skills; provide deployment support; identify repeatable implementation patterns; and collaborate with Product and Engineering. The role requires customer discovery, technical solution development, strong communication, autonomous execution, and frequent travel to customer sites.

Leads CRM data strategy, governance, quality, compliance, integrations, reporting, and analytics. Acts as the Salesforce and CRM data subject matter expert, supports AI and predictive analytics initiatives, and delivers customer, marketing, and commercial insights. The role collaborates with business and technical stakeholders, manages external partners, and coaches a CRM Data Executive while driving data capability improvements and informed decision-making.

Leads revenue performance analysis, forecasting, budgeting, business modeling, and automated reporting. Investigates revenue drivers, pressure-tests commercial assumptions, identifies structural trends, and translates complex financial and technical data into recommendations for senior stakeholders. Partners with commercial teams to improve planning quality and support revenue and margin growth.

Leads backend architecture and streaming services for high-volume maritime tracking and trade data. Builds Python and PHP microservices, Kafka pipelines, and PostgreSQL and ClickHouse data systems. Owns production reliability, observability, CI/CD, and containerized deployments while collaborating with product, platform, and client-facing teams. Mentors engineers, drives modernization, and establishes technical standards.

Design, develop, and support Azure-based cloud integrations and platform services. Build API/queue/file-based integrations, improve CI/CD and deployment reliability, troubleshoot production issues, modernize legacy systems to cloud-first patterns, and document and transfer service ownership to reduce operational risk.

Deploys, configures, and optimizes SIEM, SOAR, and other security tooling for managed security service customers. Responsibilities include customer onboarding, log ingestion, security integrations, SOC infrastructure maintenance, incident tracking, SLA management, troubleshooting, and operational improvement. The role requires collaboration with SOC analysts, engineers, customers, and service teams, with SC clearance and mandatory BPSS screening.

Lead engineer designing, developing, and troubleshooting ultra-low-latency electronic trading systems. Write high-quality C++14 production code for multithreaded, networked applications, collaborate with traders and cross-functional teams, lead engineering practices, participate across the SDLC, and drive automation and stability improvements for order routing, matching engines, market access, and risk systems.

Lead development of large-scale, real-time and historical market-data applications using KDB/Q. Drive system design, coding, performance optimization, scalability, high availability, and CI/CD automation. Mentor team members, manage delivery, partner with stakeholders and support teams, and help migrate and re-architect systems to AWS while improving operational stability and testing practices.

Design, build, and productionize autonomous and assistive multi-agent AI systems. Implement RAG and semantic search with vector databases, integrate tools/APIs, apply prompt engineering and guardrails, orchestrate microservices workflows, instrument agents for metrics, run evaluations/A-B tests, and mentor teammates.

Lead design, development, testing, release, and production support for Equity Derivatives workflows. Own production outcomes, incident triage, stakeholder communication, UAT, architecture and observability. Drive adoption of AI-assisted engineering practices, maintain release discipline, gather telemetry for stability metrics, and improve system reliability and coding hygiene through cross-functional collaboration.

Lead development of microservices that fetch, enrich, consolidate, and distribute network metadata. Design, build, test, and maintain secure, resilient production code; drive adoption of AI-assisted engineering practices; automate remediation and CI/CD; evaluate vendor solutions; coach teams on responsible AI and cloud/network technologies; lead communities of practice and ensure operational stability.

Lead platform engineer driving cloud-native microservices, developer experience tooling, IaC, CI/CD migrations, and adoption of AI-assisted engineering. Designs architectures, writes secure production code, troubleshoots systems, and mentors teams to improve reliability and delivery.

Lead development of the QES trading platform: design, build, test, and maintain production-grade software. Collaborate with front office (trading, structuring, research), deliver secure high-quality code (Python/Java/TypeScript/React), automate operational remediation, and lead agile engineering practices and communities of practice.

Support global fixed income index research by analyzing large datasets, building quantitative models, managing client projects, maintaining index operations, evaluating performance and market trends, and producing visualizations and reports to inform strategic product decisions.

Lead development and enhancement of equity derivatives trading and analytics applications, drive automation and AI-assisted engineering practices, collaborate with trading and quant teams, maintain global platform stability, and lead the Systematic Quoting Platform workstream for EMEA.

Design, develop, deploy, and maintain advanced AI products and data pipelines. Collaborate with engineers, data scientists, and product owners to deliver production-grade, secure, scalable code. Architect AI-enabled engineering workflows, improve SDLC automation, ensure compliance, and provide technical leadership and architecture governance.

Coordinate and manage delivery of technical security assessments (red/purple/penetration) across global teams. Maintain stakeholder communication, enforce SOPs, resolve SLA roadblocks, produce reports and management information, identify automation and process improvements, and build partnerships across US, UK and Singapore assessment teams.

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.

Lead development of cloud-native Python applications for global commodities trading desks. Design, build, test, and operate resilient, secure production systems; drive automation and CI/CD; evaluate vendor solutions; and mentor engineering communities of practice.

Design, build, and maintain large-scale, secure data engineering solutions. Lead architecture, deliver production code, drive automation and operational stability, mentor teams, and evaluate vendor/technology choices to advance risk technology platforms.

Lead applied AI/ML efforts to design, build, deploy, and maintain production ML services (NLP/CV focus). Collaborate with engineering, cloud, and SRE teams, research models, ensure MLOps best practices, and document processes for regulatory compliance.