Top Python Jobs in London

Design, build, deploy, and monitor scalable AI systems used across the business and by millions of members. Collaborate with product, data, and platform teams to deliver reliable software frequently. Apply software engineering, machine learning, generative AI, distributed systems, cloud infrastructure, DevOps, observability, automated testing, and performance optimization practices. Evaluate technical solutions with consideration for cost and timelines, while contributing to AI agents and multi-agent workflows.

Analyze large fan and marketing datasets using SQL, Python, Databricks, AWS, and Snowflake. Build dashboards, recurring reports, audience segments, and campaign performance tracking for international markets. Translate business questions into actionable insights, support marketing campaigns and UAT, investigate data issues, and collaborate with marketing, data engineering, international teams, and external partners. Clearly communicate findings to nontechnical stakeholders while supporting fan growth and engagement analytics.

Build and deploy AI-powered solutions for client operational problems. Responsibilities include scoping ambiguous requirements, designing LLM and retrieval workflows, developing scalable software, working with messy data, iterating with clients and operators, and creating reusable deployment infrastructure. The role combines AI engineering, software development, and technical consulting, with customer-facing collaboration, on-call responsibilities, and 25–50% travel for client engagements.

Perform manual and automated testing for geoscience software within an agile development lifecycle. Create and update test scripts, document defects, maintain automated testing code, and collaborate with developers and support teams. The role also provides product demonstrations, client support, training, documentation assistance, and testing feedback while requiring knowledge of software development, desktop and web applications, Windows/Linux, and geoscience workflows.

The Senior LNG Market Analyst maintains accurate global LNG cargo data, audits and analyzes complex trade datasets, tracks gas market events and trade flows, and identifies emerging trends. The role collaborates with Product and Engineering on platform improvements, supports sales demonstrations and client engagement, and works with News and Insights teams to anticipate market intelligence needs. It requires strong LNG market expertise, advanced Excel, SQL, Python or VBA, analytical ability, attention to detail, and presentation skills.

Design and build scalable backend systems, robust APIs, data models, and integrations using Python, GraphQL, PostgreSQL, NoSQL databases, and AWS. Collaborate within cross-functional teams, contribute to frontend applications when needed, own features through delivery, and promote maintainable engineering practices. Mentor teammates and use AI tools to improve development. Frontend experience with React, TypeScript, and Next.js, plus event-driven architecture experience, is beneficial.

Build and maintain full-stack products using Python, React, GraphQL, and modern cloud technologies. Develop APIs, integrate internal and third-party services, create performant frontend applications, and deliver robust, scalable software across browsers and devices. Collaborate within cross-functional teams, contribute to design systems and component libraries, own features from inception through delivery, and promote maintainable coding practices. Bonus experience includes TypeScript, Next.js, AWS, infrastructure as code, event-driven systems, and AI tooling.

Owns end-to-end revenue and marketing data integration, including ETL pipelines, dbt modeling, data quality monitoring, and Metabase dashboards. Analyzes SaaS revenue and marketing metrics, explains performance changes, and builds forecasting and churn-risk models. Partners with Revenue and Marketing teams to deliver reliable metrics, actionable insights, and scalable reporting.

Lead mobile security architecture, penetration testing, threat modeling, security assessments, and control implementation across Android and iOS platforms. Define secure technical strategies, develop mitigation plans, advise clients, and drive security quality and compliance. The role also contributes to mobile development, DevSecOps, reverse engineering, security research, Agile practices, technical roadmaps, and continuous improvement across front-end and back-end systems.

Leads the People Analytics data function, managing and developing analysts while delivering dashboards, data products, and complex workforce insights. Translates HR requirements into scalable technical solutions, oversees data quality and governance, defines tooling and technical strategy, and partners with HR, Finance, HRIS, and IT stakeholders. Performs hands-on analysis of complex HR datasets, including attrition, workforce trends, and diversity, equity, and inclusion.

Build and maintain secure cloud-native platforms for UK public-sector clients. Responsibilities include researching technical solutions, automating infrastructure and delivery processes, creating secure CI/CD pipelines, collaborating with developers and customers, troubleshooting systems, participating in reviews, documenting practices, and sharing technical knowledge. The role requires working four days per week on site and holding active SC clearance with eligibility for DV clearance.

Designs, deploys, optimizes, and troubleshoots cloud infrastructure for Thought Machine Vault implementations. The role partners directly with client engineering teams across the full project lifecycle, covering infrastructure preparation, high availability, disaster recovery, monitoring, security, deployment, and production support. It also contributes to presales consulting, client feedback, product improvements, and collaboration with internal engineering, SRE, architecture, and commercial teams. Travel to client sites may reach 25% of working time.

Graduate technology consultants support software development, deployments, infrastructure, system monitoring, issue resolution, testing, quality assurance, and IT service delivery. They work directly with clients on-site while developing technical skills through structured training, coaching, and industry-recognized accreditations. The role offers progression into engineering, AI, cybersecurity, information security, service desk, application support, and production support positions.

Develop and improve multi-agent Generative AI features for Pigment’s business planning platform. Build LLM-powered capabilities across the stack, collaborate on frontend, backend, infrastructure, and CI, and create reliable AI features with strong testing, auditability, and real-world product impact. Translate user needs into simple technical solutions while contributing to agent development, evaluation, and product innovation.

Conduct end-to-end ML research for options trading: design experiments, train large-scale models (LLMs/transformers), build scalable pipelines, validate and deploy models to production, and translate research into measurable P&L impact.

Customer-facing engineering role building and deploying AI-powered observability solutions. Design, implement, and support integrations, backend services, telemetry pipelines, and full-stack artifacts using Python, Java, and JavaScript/TypeScript. Drive production rollouts, troubleshooting, and codify repeatable templates and playbooks to improve adoption and product feedback.

Lead complex Professional Services engagements delivering advanced LogicMonitor integrations and automations. Design, code, test, and deploy custom solutions using APIs and cloud services, troubleshoot issues, drive product improvements, mentor engineers, and collaborate with Product, Customer Success, and Support.

Lead technical deployments of Celonis containerized solutions in customer environments. Analyze architectures, design integrations (APIs, data ingestion), implement IaC and Kubernetes-based deployments, advise on authentication/user provisioning, remove technical barriers to adoption, and collaborate with product teams to promote reusable platform solutions.

Lead deployment and onboarding of Celonis containerized solutions as the technical contact: analyze customer architectures, design integrations (APIs, data pipelines), implement Kubernetes deployments and IaC, advise on authentication/user provisioning and security, remove technical blockers, promote reuse, and collaborate with product teams to maximize adoption.

Lead analytics and measurement for performance marketing, defining KPIs, attribution models, dashboards, and experimentation frameworks. Analyze paid media effectiveness using MMM, MTA, incrementality testing, and A/B testing across channels and geographies. Partner with marketing, finance, strategy, and product stakeholders to translate complex data into actionable recommendations, build scalable SQL and Python solutions, and mentor junior analysts while establishing technical standards.

Own strategy and execution for AI-powered products, including conversational AI, agentic workflows, legal document extraction, and covenant analysis. Partner with ML engineers, data scientists, legal experts, and customers to define roadmaps, evaluate probabilistic model outputs, improve data and feedback loops, and ensure accuracy, explainability, and responsible AI practices. Lead an engineering squad while translating technical capabilities into value for financial and legal professionals.

Build and evolve 9fin’s AI platform from the ground up, supporting generative AI, agentic AI, RAG, model serving, embeddings, vector search, and intelligent automation. Develop APIs, SDKs, orchestration layers, deployment pipelines, observability, evaluation, and governance capabilities. Partner with AI and backend engineers to establish scalable architecture, developer tooling, operational standards, and reliable production AI services.

Design and build generative AI applications for complex financial and legal workflows. Lead the full model lifecycle from experimentation and training through testing, monitoring, and deployment. Apply advanced techniques across information retrieval, knowledge graphs, recommendation systems, statistical modeling, and GenAI. Collaborate cross-functionally, translate business problems into scoped initiatives, mentor teammates, promote AI adoption, and deliver production-ready solutions with strong product impact.

Backend Engineer responsible for designing systems, developing Python backend services, APIs, data processing, automation, and web application functionality. The role includes technical leadership on projects, code reviews, mentoring, experimentation, refactoring, documentation, and collaboration with product, financial, legal, and editorial teams. The engineer will work primarily with Flask, FastAPI, PostgreSQL, AWS, Lambda, Docker, and ECS.

Build production generative AI systems for complex financial and legal workflows. Responsibilities include document understanding, structured information extraction, model lifecycle management, retrieval and context engineering, data validation, evaluation, deployment, and monitoring. The role requires collaboration across teams, mentoring, product focus, and applying advanced AI research to convert legal and financial documents into reliable structured data.