Top Python Jobs in London

Own and evolve AWS and secure on-premise platforms, leading L3 production support, on-call incident response, infrastructure maintenance, automation, observability, CI/CD, security compliance, and service improvement. Build and manage Kafka, databases, identity, caching, replication, and secure data-flow services. Drive technical debt reduction and governance, support deployments and change management, align platforms with product roadmaps, and mentor junior and mid-level engineers.

Develop predictive and statistical models for Crop Protection R&D using experimental and heterogeneous datasets. Collaborate with scientific experts, support experimental design and field trials, and prototype GenAI applications including RAG, knowledge extraction, knowledge graphs, and agentic workflows. Evaluate and govern AI tools, contribute to responsible AI and data governance practices, and work with engineering teams to deploy analytical solutions.

Lead the design, development, and optimization of scalable backend services in Python and Rust. Architect distributed systems, improve reliability through monitoring and alerting, enforce testing and CI/CD best practices, and contribute to backend architecture decisions. Collaborate with product and engineering teams on complex projects, mentor engineers, and ensure the performance and stability of critical platform services.

Conduct Android malware research, reverse engineering, and static and dynamic analysis. Detect emerging threats and attack vectors, analyze applications for malicious behavior, write detection rules, develop automation, and document findings for threat intelligence reports. Collaborate across teams and share technical knowledge. Requires at least three years of relevant research, reverse engineering, or low-level development experience, programming proficiency, and familiarity with malware analysis tools.

Research and analyze fraud detection mechanisms, abuse vectors, platform vulnerabilities, and emerging fraud tactics across web, mobile, social, forum, and dark web environments. Conduct OSINT and WEBINT investigations, validate abuse scenarios, operate technical research infrastructure, analyze datasets and telemetry, automate workflows, monitor third-party channels, and deliver actionable intelligence and mitigation recommendations.

Design and build scalable Python microservices and APIs for an AI-powered code modernization and migration platform. Develop MCP servers and agent tools, orchestrate agentic and multi-agent workflows, and manage backend service lifecycles. Ensure services are robust, observable, tested, and production-ready while shaping tool-calling, state-management, and distributed-system architecture. The role also involves Git workflow automation, developer tooling, and potentially containerized deployments and agent-facing interfaces.

Build and own backend-focused full‑stack product features using Python and React; design data schemas and architecture; write well‑tested code; review peers; monitor production systems; collaborate with cross‑functional teams and integrate third‑party APIs.

Lead and grow an SDET team building reliable, scalable cloud storage solutions. Provide technical leadership, design and review architectures, plan sprints, implement deterministic functional and non-functional test suites in CI/CD/CT pipelines, collaborate on product specs, hire and mentor engineers, and continuously improve processes and systems.

Provide hands-on support for network issues, enhance workflows, focus on automation, and integrate AI in network operations.

The Windows Engineer will manage and optimize the Windows infrastructure, automate deployment processes, and collaborate globally to resolve issues and document outcomes.

Pre-sales Solutions Architect bridging product and customers: design and present AI/quantum solutions, run demos, write proposals/RFP responses, architect cloud/on-prem/hybrid AI deployments, implement MLOps and containerized LLM inference stacks, size GPUs, benchmark LLM performance, and travel as needed for customer engagements.

Design, build and deploy enterprise-scale ML and AI solutions (including LLMs and RAG) to improve operational efficiency, service resilience and customer outcomes. Perform statistical modelling, feature engineering, experimentation, and large-scale data analysis. Move models from prototype to production, support monitoring/governance, and partner with engineering, SRE, product and business stakeholders to define metrics and deliver measurable business value.

Develop, test and maintain embedded firmware for Brompton Electric bikes across the full product lifecycle. Collaborate with cross-functional teams to design and ship features, debug issues, write scalable C++ code, participate in code reviews, and support manufacturing and production releases.

Design, build, and operate internal developer platforms and production-ready infrastructure. Manage Kubernetes clusters, IaC (Terraform/Pulumi/CDK), CI/CD pipelines, secrets management (Vault), and SRE/security practices. Support AI/ML platform needs (GPU scheduling, model serving, MLOps, vector DBs) and lead client-facing technical discovery, documentation, and coaching.

Build and maintain React front-end components and responsive UIs for a control plane; orchestrate agentic harnesses (Claude) to generate, validate, and test code; contribute to Python/FastAPI back-end APIs; create templated archetypes and golden-path tooling; collaborate with UX; ensure performance, security, and testing-first maintainability.

The Senior Systems Engineer will build and maintain automation frameworks to support infrastructure operations, using tools like Terraform and Kubernetes, while collaborating with teams to enhance service delivery.

Build and operate end-to-end product features across the full stack, from design and architecture to production. Ship high-impact software, maintain code quality, work with LLMs/agents and search/OCR pipelines, and collaborate in a fast-paced, startup engineering team.

Design, build, and operate production AI systems and agents for private equity workflows. Own agent harness, tool integrations, retrieval/search, evals, and document ingestion pipelines. Ship and iterate features end-to-end to meet professional reliability and citation standards, working across backend and ML infrastructure with product and engineering teams.

Design, build, and operate backend systems for an AI platform: agentic workflows, document ingestion and search at scale, streaming execution, APIs and data models. Own features end-to-end from ideation to production, measure impact, and maintain services in production.

Design, build, and deploy intelligent AI agents for e-commerce and logistics. Develop agent architectures using ML, NLP, reinforcement learning, and multi-agent techniques; integrate with JD systems; run experiments, monitor performance, and collaborate with cross-functional teams to deliver scalable, production-ready solutions.

Support Marketplace (POP) growth by analyzing business performance, building dashboards and forecasts, monitoring KPIs (GMV, orders, revenue, conversion, fulfillment), identifying opportunities, supporting cross-functional strategic initiatives, automating reporting, and presenting insights to senior management.

Own software serviceability for humanoid robots: design and validate diagnostics, firmware/bootloader recovery, remote-diagnostics content, tooling for fast fault localization, and act as Services interface to R&D. Validate OTA, calibration, and repair procedures and support new service introductions.

Lead ownership of ML models and infrastructure lifecycle: develop, deploy, monitor, and improve ML systems. Build CI/CD for software and ML workflows, automate orchestration and environment management, ensure scalability, reliability, observability, and security, troubleshoot production issues, and document operational procedures while collaborating with engineers, data scientists, and product teams.

Execute end-to-end software release validation and regression testing on physical humanoid robots and in simulation. Design and run policy evaluations, compare sim-to-real behavior, collect reliability and performance metrics, maintain CI/CD test suites and dashboards, and ensure test data quality to determine release readiness.

Lead design and implementation of SLAM, state estimation, long-term mapping, and localization systems for humanoid robots. Integrate modern ML and foundation geometry models into navigation pipelines, build auto-labeling data workflows, deploy and benchmark spatial AI on edge hardware, and bridge research to production for robust, low-latency robot navigation in dynamic real-world environments.