Top Python Jobs in London

Develop and scale Python-based APIs, web services, mobile and voice-assistant integrations, and internal editorial systems supporting high-traffic digital products. The role involves writing clean, tested code; collaborating through reviews and paired programming; working with databases and ORM frameworks; applying RESTful and software engineering principles; and contributing to continuous integration. Experience with modern Python frameworks, GraphQL, asyncio, Docker, AWS, Kubernetes, and search platforms is advantageous.

Build and scale AI agent systems that autonomously execute workflows and integrate with enterprise data, services, vector databases, search systems, and external APIs. Develop backend infrastructure, high-throughput APIs, orchestration, memory, security, and asynchronous workflows. Ensure reliability through monitoring, observability, testing, CI/CD, and fault tolerance. Collaborate with product, research, data, and UX teams, contribute to architecture and code reviews, and develop frontend tooling for agent management.

Build and lead application security for WRITER’s enterprise AI platform. Responsibilities include threat modeling, secure architecture reviews, SAST/DAST and CI/CD security automation, code reviews, secure coding standards, penetration testing, vulnerability remediation, and protection of AI agents, data pipelines, and model training environments. The role also researches emerging LLM security threats and partners with engineering teams to embed scalable security controls.

Build secure, scalable generative AI services, applications, APIs, microservices, and agentic workflows for enterprise customers. Own system architecture from proposal through deployment, develop React and TypeScript interfaces, and partner with DevOps on continuous deployment, monitoring, logging, performance, and security. Collaborate with product, data science, and engineering teams while mentoring peers and delivering resilient production software.

Provide Tier 2 technical support for enterprise B2B SaaS customers, owning complex production issues from triage through resolution. Debug Python and no-code agents, investigate platform problems using monitoring tools, collaborate with Product, Engineering, Customer Success, and Sales, and escalate deeper issues. Build automated diagnostic tools and scripts to improve support efficiency, communicate technical concepts clearly, gather product feedback, and help customers use WRITER’s AI platform effectively.

Lead development of multimodal AI products for G2’s software marketplace. Build agent-driven user journeys, multimodal image and audio features, scalable full-stack systems, and production-quality evaluation workflows. Partner with product owners on requirements, scope, prioritization, and rapid MVP delivery. Manage, mentor, and provide technical leadership to engineers while advancing agent-first development practices.

Leads the design, implementation, maintenance, and continuous improvement of resilient infrastructure automation for algorithmic trading. Provides Linux-based electronic trading platform expertise, partners with development and infrastructure teams, manages technical risk, and supports scalable systems. The role includes technical leadership, mentoring engineers and SREs, full-lifecycle ownership, incident review, and adoption of SRE practices. Advanced Python, Unix/Linux, infrastructure automation, debugging, CI, Git, Jenkins, and software engineering expertise are required.

Build customer-specific document solutions from discovery through production, integrating Nutrient’s platform with enterprise systems and infrastructure. Deliver working prototypes quickly, measure outcomes against agreed scorecards, support sales engagements, and convert successful implementations into reusable product capabilities. The role requires strong software engineering, customer communication, cloud and infrastructure skills, production LLM experience, and comfort working in ambiguous, regulated environments with meaningful customer-site travel.

Own and improve Moneybox’s data platform, including scalable pipelines, integrations, analytical models, data quality, observability, reliability, performance, and security. Lead significant architecture changes, ingest new data sources, guide engineers and analysts, and collaborate with Engineering, Insight, Information Security, and Compliance. The role requires autonomous technical ownership, production troubleshooting, and clear communication across technical and non-technical stakeholders.

Conduct one-to-one online trial lessons for children and parents, assess needs and interests, lead simple digital activities, recommend suitable Kodland programs, address concerns, and guide families toward enrollment. The role combines teaching, communication, and consultative sales, requiring consistent part-time availability during UK peak hours and strong spoken English.

Leads development and ownership of pricing systems, actuarial models, platform infrastructure, and business processes supporting Corporate Pension Solutions. The role combines actuarial, technology, and process expertise to improve automation, operational efficiency, model strategy, outsourcing arrangements, and scalable new-business pricing. It requires actuarial expertise, software development capability, and knowledge of defined-benefit pensions, IFRS 17, Solvency UK, balance-sheet construction, and asset-liability management.

Associate Solution Engineer supporting UK customers through technical evaluations, demonstrations, proofs of concept, solution design, and implementation. Partners with sales teams, channel partners, Product Management, Engineering, Marketing, and implementation partners to communicate Snowflake’s value, develop technical champions, build architectures, and drive technical wins. Requires customer-facing presentation skills, data architecture and cloud knowledge, SQL, and the ability to solve business problems using Snowflake.

Architect, develop, deploy, and own scalable software services and API-heavy solutions for a high-throughput global payments platform. The role involves designing complex systems using serverless, event-driven microservices; improving web-service performance; mentoring junior engineers; contributing to technical interviews; and driving engineering best practices and process improvements.

Builds data-driven tools, scripts, and automation for digital media teams. The role involves discovering client challenges, contributing to workshops, designing scalable technical solutions, testing code, documenting systems, assessing failure modes, communicating with stakeholders, measuring outcomes, and supporting new business initiatives. Projects may include automated media reporting and weather-based campaign targeting.

Conduct research and develop embodied AI systems for autonomous driving, including world models, planners, reinforcement learning, reward modeling, geometric foundation models, multimodal learning, and simulation. Evaluate scaling, generalization, and sim-to-real transfer while creating benchmarks for long-horizon prediction and driving performance. Collaborate across machine learning, robotics, simulation, and deployment teams.

The Applied Scientist will develop AI systems for autonomous driving, focusing on machine learning, simulation, robotics, and real-world deployment, while advancing embodied AI technologies.

Monitor, triage, and investigate security alerts across endpoint, email, identity, and cloud environments. Support incident response, vulnerability management, remediation tracking, and security improvement activities. Analyze logs and indicators of compromise, document investigations, maintain runbooks, and collaborate with Security, IT, Engineering, and Cloud teams. Independently manage routine investigations and escalate complex incidents appropriately.

Design, build, test, and maintain end-to-end web applications and backend services. Translate customer requirements into deliverable engineering plans, develop secure and scalable features, collaborate across engineering teams, and manage functionality from testing through production. The role requires React and TypeScript expertise, REST API experience, automated testing, and a focus on clean, maintainable code and user experience.

Leads technology consulting engagements across technology strategy, operating models, digital transformation, systems selection, M&A technology due diligence, and post-deal integration or separation planning. Analyzes technology estates, evaluates platforms and vendors, develops recommendations and transformation roadmaps, supports workshops and client relationships, and contributes to proposals and practice development.

Industrial placement roles in biostatistics, clinical programming, and quantitative sciences innovation. Responsibilities include clinical trial design, statistical analysis, dataset and reporting development, quality control, machine learning, prediction modeling, and cross-functional collaboration supporting drug and vaccine development. Placements involve R, SAS, Python, GitHub, statistical methods, regulatory standards, and agile project delivery.

Lead deployment of analytics and AI into production within insurance: embed with underwriters and pricing teams, define deployment specs, ensure adoption, measure commercial impact, design monitoring and governance, and enable business users.

Designs and delivers data-driven tools, scripts, and automation solutions for digital media teams. The role involves discovering client challenges, contributing to workshops, building scalable and secure technical solutions, testing code, documenting work, measuring outcomes, and communicating with stakeholders. It also supports strategic initiatives, client presentations, case studies, new business opportunities, and project scoping. Example work includes automating media performance reporting and developing weather-based campaign targeting systems.

Develop and support valuation models for convertible bonds and other asset classes within a product development team. Responsibilities include idea generation, product specifications, UI design, manual and automated QA, client-requested feature delivery, and collaboration with quantitative developers. The role provides training in financial markets, convertible bond structures, pricing models, and front-to-back capital markets processes, with potential progression into dedicated quantitative development.

Build and deploy production-grade agentic AI applications, generative AI features, RAG pipelines, and LLM integrations for customer engagements. Develop Python and FastAPI services, model data with relational and graph databases, implement governance guardrails, and instrument systems for observability. Collaborate with platform engineering on deployment and MLOps/LLMOps, modernize legacy workflows, troubleshoot reliability issues, and contribute reusable AI patterns and best practices.

Build and improve research and production infrastructure for quantitative trading. Develop Python and C++ systems, libraries, backend services, and workflow tooling for strategy research, testing, and deployment. Improve performance, algorithmic efficiency, scalability, and distributed compute capabilities while partnering with quantitative researchers and traders. Own projects through design, implementation, testing, rollout, and ongoing enhancement.