Top Python Jobs in London

Serve as the technical bridge between product and sales: lead technical discovery, demos, and POCs; build custom integrations and demos; translate customer feedback into product requirements; create technical sales collateral; troubleshoot pre-sales and onboarding issues; monitor market and competitor trends to inform positioning.

Lead engineering to shift GTM from no-code automation to code-first, AI-agent-driven systems. Design scalable backend pipelines, integrate CRMs/APIs, build reusable agent frameworks, ensure reliability and observability, and hire/mentor a distributed engineering team to deliver production GTM infrastructure.

Design, build, and operate scalable, secure cloud infrastructure and CI/CD pipelines. Manage Kubernetes environments, implement IaC (Terraform), improve observability, troubleshoot production issues, support security/compliance, and mentor junior engineers to optimize platform reliability and cost.

Design and optimize outbound sales infrastructure and lead generation pipelines. Build automation and CRM workflows, run data-driven growth experiments, analyze campaign performance, and support sales and marketing teams to improve conversion and pipeline velocity.

Design, build, fine-tune, and deploy production-grade AI and ML systems (LLMs, RAG). Develop scalable APIs, integrate AI into business systems, monitor model performance, and collaborate with cross-functional teams.

Design, build, and optimize AI-driven automation workflows using platforms like Zapier/Make and LLMs. Integrate APIs, develop Python/JavaScript backend logic, maintain automation pipelines for sales/marketing/support, monitor systems, troubleshoot issues, and document scalable SOPs.

Design, build, and deploy AI-powered agents and workflow automations integrating with CRMs. Create prompts and conversational flows, troubleshoot integrations, optimize performance and conversions, and handle client onboarding and support in a fast-paced startup.

Design and deliver enterprise architecture and deployment blueprints for Cohesity solutions. Lead migration and transition efforts, assess risks, size and document solutions, validate deployments in the field, train partners/customers, and provide product feedback to engineering and product teams.

The Engineering Manager will lead a software engineering team, overseeing delivery, quality, and technical direction while managing development processes and fostering team growth.

Design, build and maintain cloud-based data engineering solutions and knowledge graphs using Python and AWS. Implement high-quality data pipelines, optimize performance, manage containerised workloads with Docker, and maintain CI/CD, automated testing, and collaborative enterprise data platform integrations.

Lead the operating model for the product organization, measure performance, manage product tooling, ensure go-to-market readiness, identify systemic issues, and build knowledge infrastructure.

Lead Kraken's Data Platform team focused on real-time infrastructure for data systems, managing team dynamics, architecture design, and promoting AI automation.

As a Senior Pricing Actuary, evaluate MGA opportunities for profitability, provide actuarial support, and collaborate with various teams to enhance services.

The AI Research Engineer will develop AI models to enhance product autonomy, analyze extensive data, and deliver impactful solutions, driving innovative product features.

Design and maintain Golang infrastructure services for the Confluent Cloud Platform, ensuring performance, availability, and capacity planning of the service.

As a Lead Machine Learning Engineer, you will set technical direction for ML projects, design scalable systems, mentor engineers, and drive innovation. You'll ensure successful project outcomes while balancing trade-offs and guiding team priorities.

The Principal Solutions Architect will lead presales, design AI/ML infrastructures, mentor other architects, and drive customer adoption for Nebius AI cloud solutions.

The Computer Vision Engineer will lead AI initiatives in the defense sector, delivering solutions and mentoring teams while driving technical strategy and capability development.

The Metals Insight Analyst at Kpler will conduct market research on metals and energy-transition materials, analyze supply and demand trends, create publications, and engage with clients, helping to shape the company's metals dataset and strategic insights.

Lead development of ClickHouse's Python connector and SDKs, build integrations with orchestration and transformation tools, drive AI/LLM integration strategy for production data workflows, engage with open-source community, and collaborate across product and platform teams to deliver enterprise-grade data integrations.

As a Curriculum Manager, you will manage the content development lifecycle, collaborate with instructors, and improve data science curriculum, ensuring technical accuracy and pedagogical effectiveness.

Lead the creation of Market Data Operations, manage Bloomberg and LSEG entitlements, maintain security master and identifier mappings, track enterprise data usage and costs, support exchange declarations/audits, resolve data quality issues, automate workflows, and provide stakeholder support for portfolio managers, traders, researchers and data teams.

As a Senior Software Engineer at KoBold, you'll develop innovative data systems for mineral exploration, collaborating closely with geologists and data scientists to improve exploration success rates. You'll own projects end-to-end, engage with users, and create scalable, production-quality solutions for complex geological challenges.

Design, deploy, operate and troubleshoot cloud-based and traditional media platforms (VOD, Cloud Playout). Support AWS-hosted services, metadata-driven workflows, CI/CD, integration with vendors, and migration of legacy systems. Provide technical leadership, standardise configurations, document procedures, and collaborate with Product, Platform, Software, Architecture and Operations teams to ensure reliable content delivery and continuous improvement.

Lead design, development, and operation of real-time and batch data pipelines and cloud infrastructure. Improve reliability, observability, and data architecture; own features end-to-end and mentor engineering teams while coordinating cross-team stakeholders.