Top Python Jobs in London

Own and stabilize IAM provisioning queue, build SCIM auto-provisioning and enrollment flows, automate access reviews and certification campaigns, reduce identity-related technical debt (JIT/PAM, least-privilege evidence), and integrate IAM tooling (Okta, Tines, cloud IAM) while partnering with GRC, Workplace Technology, and engineering.

Own and operate cloud infrastructure (primarily AWS) using Infrastructure as Code. Maintain and improve Terraform estates, manage Kubernetes and ArgoCD production workloads, keep CI/CD pipelines reliable, automate with Python/Bash, monitor performance, troubleshoot incidents, and collaborate with teams to deliver secure, scalable public-sector services.

Lead customer-facing AIOps engagements as a senior solutions architect: design and implement BigPanda solutions, drive enterprise implementations, mentor architects, influence stakeholders, and ensure value realization and operational resilience.

Design, implement, and maintain scalable backend services and APIs for a live mobile game platform. Ensure performance, reliability, and uptime; collaborate with DevOps, QA, data, and product teams; mentor junior engineers; participate in incident response, testing, and technical documentation.

Own end-to-end features across frontend and backend: design scalable APIs and data models, build polished React UIs, manage AWS infrastructure and CI/CD, set technical direction, and ensure performance, reliability, and security in a fast-moving startup.

Lead development and implementation of analytics and predictive models to support R&D Quality oversight across clinical, safety, laboratory, and vendor data. Build dashboards, risk indicators, automated monitoring, and audit-support tools; integrate complex data to identify portfolio-level risks and translate findings into actionable quality recommendations that support GCP/GVP/GLP/GCLP compliance and inspection readiness.

Design, develop, and enhance Cority software and client solutions. Lead technical decisions and teams, produce production-ready code, implement CI/CD, perform code reviews, mentor junior developers, collaborate with Product Owners, support and maintain systems, and own functional areas or projects.

Design, develop and maintain security automation workflows and playbooks to improve SOC detection, triage, enrichment and response. Build integrations with SIEM, SOAR, EDR, cloud platforms and APIs, implement AI-enhanced automation, produce documentation and runbooks, monitor performance, and support SOC teams and standards.

Design, build and operate Grafana Labs' bare-metal to Kubernetes platform: provision storage, networking and clusters; manage cluster networking, scheduling and autoscaling; maintain Crossplane compositions and Terraform modules; support users and run on-call duties to ensure reliability, performance, and scalability of platform infrastructure.

Lead design and operation of production-grade CI/CD and developer-facing delivery infrastructure. Contribute hands-on in Go and Python, improve pipeline reliability and speed, define paved paths and self-service Internal Developer Portal, champion progressive delivery (canaries, automated rollbacks), embed AI tooling into SDLC, and collaborate with cloud platform and engineering teams globally.

Advise AI-focused customers to design scalable AI solutions and manage large-scale GPU deployments. Deliver technical presentations, documentation, and webinars. Collaborate with engineering and product teams to prioritize and convey customer feedback.

Senior Software Engineer contributing across the full stack within a product-focused, cross-functional team. Build, deploy, and support scalable cloud-native services using event-driven architectures, improve observability and test automation, collaborate with product and customers, and champion engineering best practices to deliver high-value features.

Own cloud architecture intelligence and cost optimization: analyze cloud spend, identify inefficiencies, build dashboards, enforce governance, partner with engineering/finance to drive cost-conscious design and operations.

As a Senior Backend Engineer, you'll develop features using Python and various AWS services, focusing on AI-driven solutions for the insurance sector.

Design, build, and maintain scalable automated workflows and integrations using platforms like n8n, Zapier, Make, or Workato. Integrate systems via APIs/webhooks, troubleshoot workflow issues, monitor performance, document processes, and support data synchronization across CRMs and business tools while collaborating with cross-functional teams.

Design, build, deploy, and optimize AI/ML models and pipelines (including LLMs and RAG). Integrate models into production, work with cross-functional teams, ensure monitoring and compliance, and contribute to scalable AI systems and automation.

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, 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.