Top Python Jobs in London

Lead high-impact AI projects for energy, transition, and environment clients. Define data science approaches, design robust software architectures, develop bespoke algorithms, mentor data scientists, assess technical feasibility, plan projects, estimate timelines, and lead delivery teams. Build client relationships, translate business problems into mathematical frameworks, contribute to thought leadership, and ensure rigorous best practices throughout the project lifecycle.

Owns daily and monthly treasury reporting, cash management, liquidity monitoring, dealing activities, settlements, credit analysis, and treasury mandates. The role supports the Treasurer, manages liquidity and capital risk reporting, monitors depositor behavior, contributes to investment strategy, and helps deliver strategic banking projects. It also requires improving treasury processes, producing clear documentation, and maintaining regulatory readiness within a remote-first growth-stage bank.

Lead and grow a product engineering team building Watcher, a coding-agent security product. Responsibilities include planning delivery, managing engineers, hiring, coordinating research and engineering handoffs, handling customer integrations, making architecture decisions, reviewing code, and shipping production code primarily in Python and TypeScript. This player-coach role also establishes engineering processes, protects team focus, and uses AI-assisted tools extensively.

Own customer deployments, integrations, technical evaluations, proofs of concept, and white-glove support for Watcher, a coding-agent security product. Build integrations with coding agents, SIEMs, identity systems, and CI/CD pipelines across cloud, on-premises, and self-hosted environments. Troubleshoot customer issues, tune security monitors, communicate with technical and security leaders, and convert recurring customer needs into reusable product capabilities, documentation, and deployment tooling.

Build and operate Watcher, a full-stack coding-agent security product. Develop backend APIs, ingestion and grading pipelines, agent hooks, CLI tooling, monitoring dashboards, enterprise integrations, and real-time blocking systems. Own features from customer discovery through production deployment, while ensuring reliability, scalability, tenant isolation, encryption, access controls, and flexible cloud, on-premises, and local deployments. Collaborate with customers and security teams to improve the product and productionize monitoring research.

Leads the architecture, operation, and evolution of global multi-cloud platforms across GCP and AWS. Builds AWS landing zones, self-service developer platforms, CI/CD tooling, observability, automation, governance, and security capabilities. Supports enterprise AI transformation through platform services, guardrails, and operational patterns for AI applications and agentic workflows. Provides technical leadership during incidents, evaluates emerging technologies, mentors engineers, and drives reliability, cost efficiency, developer experience, and engineering standards across distributed teams.

Lead ML Engineer to design and build MCP servers, Skills, and agentic orchestration for an enterprise agent platform. Implement APIs, secure wrappers, RAG and prompt-based flows, deploy on containerised/Kubernetes platforms, and shape developer patterns, governance, and operational readiness while partnering with product teams, SRE and QA.

Own Intropic’s security stack across AWS and GCP cloud infrastructure, endpoints, detection and response, threat modeling, CI/CD security, SaaS integrations, AI agent security, patching, SOC 2, penetration testing, security policies, IT access, and endpoint management. The role combines hands-on security engineering with GRC and IT responsibilities, including out-of-hours incident response and automation.

As a Senior Azure Data Engineer, you'll design and deploy data engineering pipelines using Databricks on Azure, collaborate with clients, and implement best practices in a consulting environment.

Lead architecture and delivery of data solutions on Databricks within Azure, ensuring best practices in data pipeline design and implementation.

The role involves designing and building data pipelines using AWS technologies, leading projects, and mentoring junior engineers in a data engineering context for financial services.

Design and build cloud-based data pipelines using AWS tools, collaborate with clients, ensure data governance, and mentor junior engineers.

Design and build Index Cloud, a globally distributed, multi-tenant compute platform across Kubernetes, bare-metal, and public cloud infrastructure. Own architectural decisions, infrastructure-as-code frameworks, platform APIs, SDKs, deployment systems, networking, storage, and distributed systems solutions. Drive technical strategy through RFCs and design reviews, improve developer productivity with self-service tooling, and mentor engineers across multiple teams.

Design and build Index Cloud, a globally distributed, multi-tenant platform operating across bare-metal and public cloud infrastructure. Responsibilities include architecting Kubernetes clusters, infrastructure-as-code frameworks, deployment systems, platform APIs, SDKs, and distributed systems. The role drives technical strategy through RFCs and design reviews, improves developer self-service, establishes security and tooling standards, mentors engineers, and collaborates across SRE, networking, security, operations, and software engineering teams.

Own the reliability, performance, resilience, observability, automation, and security of enterprise network infrastructure. Design and maintain Cisco and Arista datacenter networks, support WAN connectivity, automate operations with Python and Ansible, extend infrastructure-as-code and CI/CD practices, and lead incident response, on-call operations, postmortems, and root-cause analysis for complex network issues.

Build and maintain a full-stack analytics workflow application using Angular, Python, and FastAPI. Develop data pipelines and models with pandas and NumPy on Snowflake and Azure. Coordinate an offshore vendor team, manage delivery priorities and spending, use AI coding assistants, and translate business requirements into reliable enterprise software for stakeholders.

Own CFC’s cyber catastrophe modelling and exposure management approach, developing and calibrating proprietary models to reflect emerging threats, claims trends, and changing risk drivers. Analyze portfolio performance and exposure, translating complex data into commercial insight for underwriting strategy, growth, business planning, and risk appetite. Collaborate with underwriting, cybersecurity, claims, and performance teams, provide training and guidance, and contribute to strategic projects.

Lead and develop a team of 4–8+ engineers responsible for delivering product or platform outcomes. Own planning, execution, release quality, stakeholder alignment, technical standards, hiring, performance management, career development, and team effectiveness. Partner with Product, Design, and modelling teams to build mobile and backend features incorporating AI/ML capabilities. Drive high-quality, scalable systems and organization-wide engineering improvements in a fast-paced product environment.

Build and deploy enterprise agentic AI solutions using Agentforce Operations, multi-agent orchestration, RAG, vector search, APIs, and enterprise integrations. Develop production code, data grounding systems, ETL/ELT pipelines, observability dashboards, and secure connections to Salesforce, cloud platforms, and ERP systems. Collaborate directly with enterprise customers and internal product teams, provide architecture guidance to executives, and convert deployment learnings into reusable accelerators. Travel 25–30% for onsite customer deployments.

Build and deploy Salesforce Data 360 solutions in enterprise customer environments. Responsibilities include developing ingestion pipelines, data models, identity resolution, integrations, retrieval systems, vector search, and agent communication protocols. The role involves coding with SQL, Python, Apex, and related tools; testing security and scalability; debugging data and API issues; implementing OAuth and SAML controls; collaborating with customers and partners; supporting production handoff; and documenting reusable implementations and platform gaps.

Designs and implements complex Cisco data centre and networking solutions for enterprise customers. Responsibilities include deploying Nexus, VXLAN, and ACI environments; integrating security and network service appliances; analyzing performance; resolving complex technical issues; automating deployments with AI and infrastructure-as-code practices; developing reusable delivery frameworks; and influencing product roadmaps. The role is customer-facing and requires deep networking expertise, consulting or service delivery experience, and professional-level certifications.

Manage software quality engineers testing and deploying high-performance European trading systems. Lead test planning, staffing, automated regression testing, code reviews, test framework development, CI/CD infrastructure, dashboards, and reporting. Apply AI techniques to QA, guide team development, and collaborate with engineering and business teams. Develop trading-system test scenarios across equities, options, futures, and indices while improving system performance, reliability, and testability.

Own the full technical relationship for a strategic global healthcare account, from discovery and proof of concept through technical close and expansion. Architect and demonstrate Snowflake solutions for clinical interoperability, claims, population health, real-world evidence, and healthcare AI/ML. Advise senior healthcare technology leaders, translate regulatory requirements into production solutions, coordinate internal teams, develop account success plans, and mentor junior Solution Engineers.

Lead end-to-end data science and machine learning solutions for dynamic content targeting, from business conception through production deployment and impact evaluation. Partner with stakeholders, improve model quality and lifecycle processes, use model outputs to guide user experiences, and explore emerging AI techniques. The role requires advanced Python, SQL, dbt, statistical modeling, production ML deployment, and clear communication with technical and non-technical audiences.

As an Observability Engineer, you'll design systems for telemetry management, build scalable pipelines, and contribute to industry observability standards. Responsibilities include extending OpenTelemetry and enhancing incident response with telemetry data.