Top Python Jobs in London

Build full-stack, low-latency trading and pricing tools for options traders. Collaborate with traders, researchers, and business stakeholders to design intuitive frontends and scalable backend services, prototype and productionize distributed systems, and expand trading capabilities globally while improving performance, stability, and usability.

Design, build, and operate globally distributed storage systems; own code from design to release; provision and benchmark storage hardware; model failure domains; build observability, runbooks, and automation; collaborate across teams to ensure reliability, performance, and scalability.

Founding full-stack engineer responsible for building and owning the platform’s frontend, backend, APIs, integrations, and cloud architecture. The role involves making technical decisions, developing secure and scalable Python services, collaborating with founders on the product roadmap, and delivering rapidly in an ambiguous early-stage startup environment. This is the company’s first engineering hire, with potential progression to VP of Engineering.

Build and maintain Ergodic AI’s AI platform across back-end and front-end systems. The role involves developing with Python web frameworks and JavaScript/TypeScript, integrating with client technology stacks and workflows, applying AI, ML, and LLM concepts, and contributing to DevOps, cloud deployment, testing, and infrastructure practices. As an early-stage hire, the engineer will help shape the product and solve complex data and AI challenges.

Build foundational systems for AI models across data modalities, develop agentic systems and specialized models, and implement reinforcement learning and active inference solutions. The role involves hands-on architecture and product development, requiring Python backend expertise, cloud deployment knowledge, DevOps practices, and the ability to contribute across the technical stack in an early-stage startup.

Analyze large datasets, apply statistical and machine learning models, perform data analytics, and create visualizations. Collaborate with founders and enterprise clients to solve complex business problems, embedding developed models into the Kepler AI platform. This early-stage role requires hands-on development, strong analytical communication, and comfort working in an ambiguous startup environment.

Develop cloud-based Java microservices for CC Responder using agile Scrum practices. Responsibilities include full software development lifecycle ownership, system integration, testing, documentation, customer support, mentoring junior engineers, code reviews, architectural guidance, and establishing code quality standards.

Integrate security into software delivery and infrastructure workflows across AWS and GCP. Build scanning into CI/CD pipelines, maintain security guardrails, secure containerized workloads, implement least-privilege access and secrets management, and support compliance with SC TRM and BNM RMiT. Improve monitoring, vulnerability reporting, incident readiness, and secure delivery practices while collaborating with platform and engineering teams using multiple programming languages.

Design and build scalable Python backend systems for a real-time AI voice-agent platform. Responsibilities include architecting microservices, APIs, distributed systems, databases, message queues, event-driven workflows, EHR integrations, observability, and HIPAA-compliant infrastructure. The engineer will own backend features end to end, ensure reliability and low latency at scale, and collaborate through technical discussions and code reviews.

Build and scale a distributed platform supporting engineering simulations, agentic applications, and physical AI workflows. Responsibilities include designing distributed architecture, developing production Python services, optimizing distributed compute, implementing workflow orchestration, and contributing to CI/CD, testing, deployment, observability, reliability, and incident response. The role also involves mentoring engineers, making technical decisions, collaborating cross-functionally, interviewing candidates, and supporting end-to-end platform operations.

Lead the architectural evolution of an AI platform from monolithic to distributed systems. Design agent-ready services, write production Python, build distributed compute and workflow orchestration, and own CI/CD, testing, deployment, observability, reliability, and scaling. Mentor engineers, establish technical standards, guide cross-team decisions, collaborate with stakeholders, and support hiring. The role requires deep distributed systems, Kubernetes, AWS, workflow orchestration, data processing, security, and production reliability expertise.

Provides economic crime consulting services, including regulatory benchmarking, risk assessments, target operating model design, control implementation, technology optimization, data quality and integration, and change program delivery. The role supports KYC, transaction monitoring, customer and payment screening initiatives while translating regulatory requirements into business, process, data, and system changes. It also contributes to client relationships and the growth of the firm’s economic crime consulting capability.

Lead end-to-end AI and technology consulting engagements, from opportunity shaping and client advisory through delivery governance and team leadership. Design and deliver production-grade AI/ML, LLM, software, and cloud solutions, including agentic systems, MLOps, monitoring, cloud architecture, APIs, front-end applications, testing, security, and CI/CD. Apply deep technical expertise while communicating effectively with technical and non-technical stakeholders and supporting practice growth.

Lead delivery coherence for a strategic investment platform across engineering, quantitative, infrastructure, IT, and business teams. Manage dependencies, testing strategies, environments, risks, integration challenges, delivery evidence, performance benchmarks, stakeholder communications, prioritization, and resourcing. The role requires experience in investment banking or quantitative finance, exposure to quantitative investment strategies and systematic platforms, collaboration with quant researchers and developers, and technical fluency across architecture, infrastructure, and integration.

Lead and support live broadcast delivery for major sporting events across on-premise and cloud environments, primarily AWS. Monitor, troubleshoot, and optimize video workflows; coordinate timelines, requirements, and stakeholders; develop Python automation; support reporting and knowledge sharing; and travel internationally for event deployments. The role includes irregular evening and weekend hours during live events.

Lead the architecture, development, evaluation, and production deployment of enterprise AI systems and agentic applications. Build solutions using LLMs, retrieval, orchestration, APIs, data systems, and cloud infrastructure. Guide engineers, mentor teams, work directly with customers, translate business workflows into reliable AI products, and establish reusable deployment patterns. The role also involves model evaluation, monitoring, production readiness, and sharing field insights with product and research teams.

Lead enterprise architecture for SAP S/4HANA transformation programs, including process redesign, solution architecture, portfolio management, integration, governance, and technology strategy. Partner with business and technology leaders, product managers, engineering teams, PMO staff, system integrators, and software providers. Evaluate architectures, software standards, business cases, security and privacy requirements, regulatory alignment, technology roadmaps, and SAP ECC-to-S/4HANA migration plans.

Build and scale internal systems and tooling for a large social gaming platform. Responsibilities include collaborating cross-functionally, delivering software in an agile environment, troubleshooting systems, managing risk through DevOps and testing, improving development processes, and maintaining secure, reliable, scalable services. The role requires frontend and backend development, including React, WordPress, Python, and Golang, plus expertise in microservices, event-driven systems, and distributed computing.

Customer-facing Threat Analyst supporting financial institutions with fraud detection, behavioral biometrics, and threat prevention. Responsibilities include advanced analytics, customer consulting, fraud strategy, SQL-based reporting, rule deployment, proof-of-value analysis, workshops, emerging-threat research, and sales enablement. The role partners with customers, Data Science, Sales, and Product teams to improve fraud detection while minimizing customer friction. Remote role based preferably in the UK, with travel across EMEA approximately twice monthly.

As a Model Developer, you will deliver end-to-end model solutions using Python, collaborate with actuarial teams, mentor juniors, and improve model development practices.

As an Applied AI Engineer, you will build AI applications for public sector clients, create and evaluate datasets, and collaborate with teams to address challenges using AI solutions.

Provide technical expertise to customers deploying and integrating Shield AI's Hivemind autonomy software. Develop autonomy applications, deploy AI infrastructure at customer sites, train and support customers, debug API integrations, collaborate with product/engineering, create documentation and training materials, and assist sales. Travel to customer sites (~30%).

Integrate and deploy autonomy software onto unmanned aircraft, prepare flight-ready systems, support on-site flight tests, debug hardware/software, capture and analyze flight data, collaborate with autonomy/GNC/test teams, and support certification and continuous improvement for reliable autonomous operations.

Lead and develop a team of Forward Deployed Engineers to execute customer onboarding, on-site deployments, troubleshooting, and sustained adoption of the Hivemind SDK. Drive field feedback into product, translate mission goals into technical milestones, and partner with engineering and product teams to improve deployment readiness and customer outcomes.

Integrate autonomy software onto unmanned aircraft, prepare flight-ready systems, support on-site flight tests, debug hardware/software issues, capture and analyze flight data, collaborate with autonomy/GNC/systems teams, and support certification and continuous improvement for mission deployments.