Top AWS Jobs in London

Work as a hands-on mid-level full-stack engineer building and shipping features across frontend and backend. Contribute to code quality, reliability, and architecture, collaborate with senior engineers through reviews and pairing, and participate in product and technical planning within a small, growth-focused SaaS team.

Client-facing Enterprise Data Architect designing AI-ready data estates. Assess and modernize data platforms (lakehouse/warehouse), define governance, metadata, semantic models, lineage and data products, advise on platform choices and RAG/vector patterns, and produce target architectures and implementation roadmaps while engaging senior stakeholders.

Transform procurement, cloud and infrastructure data into dashboards, forecasts and insights to support capacity planning, supplier management, cost optimisation and investment decisions. Build ETL pipelines, KPI frameworks and automated reporting, partnering with procurement, finance, engineering and operations and presenting findings to senior stakeholders.

Lead FTSE Russell's enterprise data strategy, governance, quality, lineage and target-state architecture. Build and run a Data Management function, drive large-scale data transformation and analytics programmes, embed change management, and partner with business, tech, risk and compliance to reduce data risk and improve data-driven outcomes.

Lead and deliver data warehouse and pipeline solutions for Group Risk. Design, review and implement resilient ETL/data engineering processes, supervise a team, collaborate with stakeholders, and drive development using Python, DBT and Airflow while ensuring high code quality and test-driven practices.

Lead and grow a 5-7 person front-end team to design, architect and deliver a greenfield React-based Unified Client Experience using AWS, micro-frontends, module federation and modern CI/CD. Own people management, technical standards, integrations (GraphQL), quality, observability, security, and stakeholder collaboration to deliver performant, accessible web applications in a regulated financial environment.

Lead design and implementation of generative AI solutions: prototype LLM/RAG/agent systems, integrate models with APIs and data sources, deploy cloud-native production services, apply LLMOps, and collaborate across product, design, and engineering teams.

Ensure availability, reliability and scalability of AWS-based services. Manage IaC, CI/CD for containerised and serverless apps, monitor with Prometheus/Grafana/CloudWatch, respond to incidents, drive cost optimisation and platform improvements.

As a Generative BI & Insight Manager, you'll design and optimize solutions, monitor performance, and align capabilities with client business goals, emphasizing generative AI and BI.

Work on platform engineering to build, automate and maintain cloud infrastructure and platform components; support operational excellence through on-call rotations, incident management, CI/CD, monitoring, and BAU; collaborate with engineering and data teams to design secure, scalable systems and reduce operational toil.

Own end-to-end customer deployments of Sierra's AI platform: architect, deploy, upgrade, and operate infrastructure in customer cloud environments. Define standards, tooling, runbooks, and automation for repeatable deployments while partnering with engineering, product, sales, and customer teams to meet security, compliance, and operational requirements.

The Senior Business Analyst will liaise between customers and tech teams, analyze business needs, gather requirements, assist in project management, support implementation, and enhance internal products.

Build and manage multiple datasets, create automated ETL pipelines, integrate datasets, and ensure data quality for QRT's research and trading platform.

The Machine Learning Engineer will develop AI-driven features, deploy scalable systems, and enhance reliability while collaborating with teams to integrate AI solutions.

Join Depop as a Senior Machine Learning Engineer to design and implement ML pipelines for recommendations, collaborating with teams to enhance product personalization.

Depop seeks a Senior Machine Learning Engineer for the Ranking team to develop and maintain machine learning systems for personalized rankings. Responsibilities include designing training pipelines, collaborating with ML scientists, and optimizing model serving systems.

The Cheminformatics Engineer will develop AI methods and software solutions to enhance drug design productivity, collaborating across teams and managing the software lifecycle.

The Immunoinformatics Engineer will develop AI methods for drug discovery, collaborate with teams, and manage software lifecycle while staying updated on relevant scientific advancements.

Lead Machine Learning Engineer to oversee AI projects, guide technical direction, manage teams, and innovate in building scalable ML systems.

Lead the development and deployment of scalable AI systems, mentor junior engineers, and collaborate with teams to solve client challenges.

The Head of Data at CreateFuture is responsible for the Data capability's strategy, execution, and performance, guiding data engineering, analytics, data science, and AI solutions while ensuring client engagement and commercial impact.

The Backend Engineer will write high-quality Go code, implement microservices, manage legacy service migration, and optimize system performance.

Develop and maintain scalable backend services, focusing on TDD, DDD, and CI/CD. Collaborate with teams to optimize systems and code quality.

The Senior Backend Engineer will develop scalable backend services using Go, optimize systems for performance, and collaborate with teams on technical designs.

You will design scalable systems, develop backend services, lead architecture efforts, and integrate AI/ML solutions while ensuring system reliability and performance.