Top Python Jobs in London

The Senior Application Developer will create applications on D-Wave's quantum computers, collaborate with stakeholders, and solve complex problems using algorithms in Python.

The Senior Sales Engineer at MariaDB will manage technical sales processes, design solutions for clients, and collaborate with sales to close deals in the EMEA region.

Monitor and analyze customer vulnerability and asset risk data using Qualys TruRisk; research threats and exploits; produce reports and briefings; track remediation; onboard environments; escalate high-risk findings; improve playbooks and processes.

Lead teams to design, architect, provision, migrate, operate and govern hybrid cloud and on-premise infrastructure. Deliver strategies, automation, security, resilience and lifecycle management for enterprise-scale transformations.

Lead design and delivery of AI-ready infrastructure across on-prem, colocation and cloud. Define GPU compute architectures, ensure secure scalable GPU platforms for training, fine-tuning and inference, and manage distributed architecture and engineering teams during hybrid cloud transformations.

Design, build, migrate, operate and govern hybrid cloud and on-prem infrastructure. Architect and deliver cloud transformations, implement virtualization, container platforms, automation, and resilience strategies.

Design, implement, and optimize enterprise LAN/WAN/WiFi and cloud network architectures. Lead cloud networking (AWS/Azure/GCP), automation (Ansible, Python, Terraform), monitoring, troubleshooting, and enforce security/compliance. Collaborate with cross-functional teams and mentor junior engineers.

Ingest, transform, harmonise and quality-control large genomic datasets (GWAS, genotypes, phenotypes). Configure pipelines, interpret QC diagnostics, investigate anomalies, curate metadata, and collaborate with engineering and science teams to expand genomic data resources and schemas.

Design, build, test and maintain enterprise applications using Microsoft Power Platform and related technologies. Lead design and code reviews, gather and prioritise stakeholder requirements, support system integrations, plan releases, troubleshoot production issues, and promote quality, security and continuous improvement across the product team.

Responsible for deploying, operating, and ensuring reliability of a centralized AI-SDLC platform. Build/manage infrastructure, CI/CD pipelines, observability, security/compliance controls, and provide operational/on-call support to meet enterprise SLAs while optimizing cost and scalability.

Build and maintain production data pipelines and systems in Python; lead technical direction for the Insights platform; improve engineering standards, observability, and data quality; apply AI across products and pipelines; help develop AI-ready data foundations such as semantic layers.

Define and operationalise scalable platform services and delivery-readiness frameworks. Lead a Platform Services Engineer, collaborate with Product Engineering to translate product capabilities into repeatable service offerings, manage documentation/version control, drive automation and continuous improvement (AI-first mindset), and establish service standards, SLAs, and enablement for global deployment.

Design, build, and maintain production AI workflows integrating HR, Finance, Operations, and CRM. Implement orchestration, agents, prompts, retrieval pipelines, and evaluation/monitoring to ensure reliable, auditable decision-making. Iterate on model behaviour using feedback and metrics, partner with Data Engineering on infrastructure, CI/CD, and governance, and own decision quality and outcomes.

Lead design and implementation of CI/CD pipelines, infrastructure automation (Ansible/Terraform), and containerised platforms (Docker/Kubernetes/EKS/AKS) on AWS. Monitor and optimize systems (DataDog), ensure security/compliance, troubleshoot environments, mentor engineers, and drive POCs for AI-assisted automation integrated into CI/CD, code validation, and incident resolution.

Research and engineer large multimodal and reinforcement-learning models for robotic agents: design, train, evaluate models; prototype in simulation and on hardware; build data pipelines, simulation environments, and distributed training infrastructure; collaborate to scale promising approaches into production and publish results.

Design and build research prototypes and production-capable systems to enable portable, interoperable agent and model workflows. Develop model routing, provider abstractions, memory and context representations, benchmarking suites, and evaluation protocols. Run ML experiments, implement robust APIs and integration layers, collaborate across research and engineering, and communicate results via reports, demos, publications, and open-source releases.

Lead valuation and modeling of complex derivatives and illiquid instruments using Monte Carlo, binomial trees, option pricing, and securitisation waterfall models. Manage client engagements and a team of junior quants, produce technical reports, and implement models using Excel/VBA, Python, C#/C++, and vendor tools like Bloomberg and Numerix.

Lead development and scaling of the Payments Experience web application and platform tooling. Design services via RFCs, own end-to-end development, containerization, deployment, and maintenance. Ensure test coverage, observability, CI/CD and IaC. Mentor junior engineers and collaborate cross-functionally to deliver high-quality, customer-facing features.

Design and build reliable systems, manage technical projects, write high-quality Python code, and collaborate with researchers to deliver functional software solutions.

As an Engineering Manager, you will lead engineering teams, ensuring high performance and delivery of customer value while driving technical decision-making and managing project outcomes in a cross-functional environment.

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 top-of-funnel growth for a B2B fintech SaaS: design self-sustaining paid and organic acquisition loops, run weekly A/B and multivariate experiments, lead website CRO with heatmaps/session recordings, build lead-capture tools, run ABM plays with Sales, and own the analytics stack (UTM, GA4, attribution) using SQL/Python and BI tools to track CAC/CPL and optimize conversion.