Top AWS Jobs in London

Develop and maintain full-stack Trading and Pricing applications. Translate business needs into technical requirements, design and implement React, Django, and Python solutions, integrate APIs and databases, test and deploy software, and support production releases. Collaborate with stakeholders and engineering teams on architecture, Agile delivery, CI/CD, cloud infrastructure, Terraform, and serverless services.

Develop high-performance iOS and Android applications and backend services for athlete performance. Build low-latency communication interfaces that stream sensor and optical tracking data to cloud and mobile clients, translating complex biomechanical data into actionable metrics. Collaborate with Engineering, QA, Product, Design, and Scrum teams; write quality code, conduct reviews, test ideas, and contribute to mobile, cloud, real-time data, and application architecture.

Leads the Communications Platform engineering team, building scalable, highly available communication services across email, SMS, WhatsApp, and other channels. Responsibilities include team growth, roadmap and delivery ownership, architecture leadership, production stability, CI/CD, observability, hiring, cross-functional collaboration, and responsible AI adoption. The role also oversees the public website and requires experience with distributed systems, AWS, APIs, multi-vendor integrations, fintech, and regulated financial services.

Maintains and supports large-scale AWS, datacenter, and production infrastructure across Windows, Linux, VMware, and physical platforms. Responsibilities include monitoring systems, resolving incidents, administering enterprise services, patching and provisioning servers, managing identity and access, optimizing performance, supporting capacity planning, and participating in on-call operations. The role also includes datacenter hardware activities, vendor coordination, security compliance, and infrastructure automation.

Leads enterprise new-business sales across the UK and Northern Europe, managing approximately five account executives. Responsibilities include recruiting and coaching talent, engaging CXO prospects, developing partner channels, building pipeline, forecasting, driving sales strategy, and collaborating with sales engineering, marketing, operations, and product teams. The role requires significant enterprise software sales leadership experience, expertise in automation or GenAI, and willingness to travel up to 50%.

Leads strategic market-modeling projects from discovery through implementation for live insurance pricing. Develops and improves statistical and machine learning models, ensures governance and fair customer outcomes, and collaborates with pricing, underwriting, data, and ML engineering teams. The role owns complex analytical problems, supports model deployment, mentors junior colleagues, and communicates technical recommendations to varied audiences.

Leads the platform engineering function, owning strategy, internal developer platforms, self-service tooling, CI/CD, infrastructure, observability, reliability, and data operations. Builds and mentors platform and data operations teams while remaining hands-on with coding, design reviews, and prototyping. Establishes reliable data pipelines, security and cost controls, developer experience metrics, incident practices, and technical roadmaps aligned with business goals.

Leads end-to-end performance testing and assurance for complex digital services. Owns strategy, risk assessment, test delivery, readiness recommendations, and production assurance while mentoring performance testers. Provides performance engineering and architectural expertise across load, stress, soak, scalability, and resilience testing. Supports Gatling migration, CI/CD integration, automation, tooling, root-cause analysis, governance, and stakeholder engagement in complex or regulated environments.

Develop and deploy data science, machine learning, and AI solutions for secure government and intelligence environments. Responsibilities include predictive modelling, NLP, graph analytics, data integration, anomaly detection, model validation, dashboards, and production deployment. The role collaborates with engineering and operational teams to deliver automated insights and decision-support capabilities, while contributing to AI/ML strategy and technical roadmaps.

Designs, implements, operates, and maintains Marex’s global network infrastructure. Responsibilities include network consultancy, operational support, security design, troubleshooting, vendor management, cloud networking, automation, infrastructure as code, and reporting. The role supports WAN, campus LAN, firewalls, exchange connectivity, and low-latency networks while ensuring regulatory compliance and operational resilience.

Design and maintain end-to-end automated testing across AWS web applications and Salesforce workflows. Build cross-platform UI and API automation for deployments, metadata backups, integrations, webhooks, and secure queues. Create resilient Salesforce Lightning tests, validate data with REST APIs and SOQL, and integrate automation into Git-based CI/CD pipelines.

Partners with Sales and Customer Success to qualify opportunities, demonstrate Avid video production solutions, lead proof-of-concept engagements, and align products with post-production workflows. Builds and maintains demo systems, gathers requirements, supports quotes and technical documentation, updates Salesforce, and advises customers on cloud architectures and data insights. Requires strong post-production expertise, technical knowledge of networking and security, and up to 40% international travel.

Build and operate backend services and streaming data pipelines that ingest sensor, rail, and waterway data into Kpler’s commodities intelligence platform. Responsibilities include developing Python and FastAPI services, maintaining Kafka and Airflow pipelines, validating time-series data, deploying cloud services, monitoring systems, improving CI/CD, supporting customer-facing applications, and participating in on-call operations.

Build end-to-end data, analytics, machine learning, generative AI, and agent-based solutions. Develop predictive models, conduct experiments, analyze trends, create insights, and support governed, secure, scalable data platforms. Collaborate in agile teams while applying data management, privacy, risk controls, and compliance practices. The program includes mentorship and training for students pursuing quantitative or technical degrees.

Design and maintain scalable backend systems using Kotlin and Spring Boot. Lead architecture and technical design, develop secure REST APIs, improve engineering quality through testing and automation, and guide delivery across multiple initiatives. Mentor engineers, collaborate with clients and cross-functional teams, evaluate emerging technologies and AI capabilities, and promote resilient, maintainable software practices.

Analyze, clean, validate, and reconcile data from multiple sources; write SQL; maintain databases; build dashboards, reports, and KPIs; investigate discrepancies and integration failures; support migrations and data pipelines; and provide UK/Europe clients with data-related support. The role also requires documenting incidents, explaining technical findings to non-technical stakeholders, monitoring processing jobs, and collaborating with Product, Engineering, and Program Management.

Develop and enhance Java applications, translate complex requirements into technical specifications, and build scalable cloud-native solutions using Spring Boot, Kafka, AWS, and microservices. The role includes implementing architecture patterns, writing comprehensive automated tests, working with relational and non-relational databases, supporting CI/CD, addressing information security and data privacy requirements, and mentoring junior developers.

Drive net-new enterprise sales among AI-native startups in London. Build executive relationships with founders, venture capitalists, developers, and technical leaders; develop data-driven go-to-market strategies; manage complex, multi-stakeholder sales cycles; establish strategic partnerships; exceed revenue targets; and evangelize MongoDB products and partner technologies.

Develop backend services and APIs powering AI and generative AI tools, while improving search performance, scalability, and reliability. Design data flows, integrate ML services, work with Elasticsearch and PostgreSQL, and contribute to architecture, access control, and visualization infrastructure. Lead code reviews, mentor engineers, refactor systems, document solutions, and own projects through delivery while collaborating with product, design, data science, and business teams.

Build and maintain CI/CD pipelines, cloud and on-premise infrastructure, infrastructure-as-code, monitoring, alerting, and logging for trading and business systems. Support developers with build, deployment, and environment issues; automate repetitive tasks through scripting; improve software delivery practices; investigate incidents; and participate in an on-call rotation. The role requires experience with GitHub Actions, containers, Terraform, cloud platforms, networking, and Python, PowerShell, or Bash.

Drive enterprise sales across major financial services institutions in London. Build strategic territory plans, develop C-level relationships, manage complex sales cycles from prospecting through closing, and grow new and existing accounts. Position Neo4j’s graph intelligence platform for data, AI/ML, fraud, and risk use cases. Partner with solution engineering, marketing, customer success, professional services, cloud providers, and technology partners while maintaining accurate CRM and forecasting data.

Design and deliver data architectures, cloud platforms, pipelines, integration frameworks, and governance practices for regulated-industry clients. Advise on data strategies, operating models, lakehouses, warehouses, data mesh, and AI-ready ecosystems. Lead transformation engagements, support pre-sales and thought leadership, mentor consultants and engineers, and maintain expertise in emerging data, cloud, analytics, and AI technologies.

Build and deploy production-grade machine learning software, tools, infrastructure, and scalable reusable solutions. Collaborate with engineers, data scientists, commercial leads, clients, and partners to solve complex challenges. Lead technical scoping, architecture, ML deployment standards, and customer advisory activities while translating technical concepts for non-technical stakeholders.

Build and deploy production-grade machine learning software, tools, infrastructure, and scalable solutions. Collaborate with engineers, data scientists, commercial leads, clients, and partners to solve complex challenges. Lead technical scoping, architecture decisions, and ML deployment standards while advising technical and non-technical stakeholders on production AI systems.

Build and scale AI-powered systems in cross-functional teams. Responsibilities include developing scalable frontend and backend architectures, deploying machine learning outputs into production, building data pipelines and cloud infrastructure, and advising customers on complex technical requirements. The role requires ownership across the application lifecycle, balancing rapid prototyping with maintainability, and collaborating with data scientists and product managers.