Top AWS Jobs in London

Customer-facing engineering role that designs, builds, and productionizes end-to-end data and AI solutions on Databricks. Lead architecture and implementation of data pipelines, ML/AI model integration, and user-facing applications, collaborate cross-functionally, deliver production deployments, provide customer training and support, and contribute reusable assets and product feedback.

Lead architecture and platform strategy for high-volume, data-intensive distributed systems using Domain-Driven Design. Provide project-embedded consultation, define standards (naming, protocols, patterns), improve platform capabilities, and communicate technical decisions to stakeholders. Drive CI/CD automation, cloud-native operations, and reliability/availability-focused design while selecting third-party components and ensuring security-conscious engineering.

Design and implement high-performance client-side web applications using Angular and TypeScript. Collaborate with product and backend teams to integrate RESTful APIs, apply TDD and unit testing, conduct peer reviews, and experiment with AI tooling to accelerate development of cloud-based 3D visualization tools.

Sell Databricks Data Intelligence Platform into large financial services accounts. Develop industry-specific use cases, co-develop business plans with partners, drive adoption of usage-based subscriptions, manage executive relationships, lead cross-functional teams, and close complex enterprise deals to exceed bookings and usage targets.

Lead EMEA paid Priority Support end-to-end: own regional revenue targets, scale and coach the Designated Support Engineer team, drive proactive AI-augmented advisory engagements, partner with Sales and reactive support for escalations, and ensure customer retention, consumption growth, and delivery quality.

Lead architecture and strategic evolution of hybrid infrastructure platforms (VCF, storage, VDI, backup, hybrid cloud). Define reference architectures, automation and observability standards, guide major programmes and migrations, troubleshoot complex incidents, and mentor infrastructure engineers to ensure secure, resilient, and operationally supportable platforms.

Lead design and delivery of production-grade data pipelines, models and analytics on cloud platforms. Translate ambiguous problems into technical solutions, build/operate ETL/streaming, embed governance, integrate ML, apply software engineering practices, and communicate insights with visualisations and consultancy-grade materials.

Lead cloud-native and hybrid enterprise architecture programs, advising CIO/CTO, embedding GenAI and agentic assistants, owning design authority and governance, integrating LLM platforms and LLMOps, ensuring security, observability, AIOps and FinOps, driving commercial origination and leading architect/engineering teams to delivery excellence.

Develop and maintain back-end services (Java/Kotlin, Spring Boot) and front-end features (HTML/CSS/JS/TypeScript, React/Angular), build REST APIs, work with relational and NoSQL databases, write automated tests, use Git and CI/CD, and follow secure, accessible engineering practices in an agile team supporting public-sector systems.

Act as a trusted advisor to customers, lead technical onboarding and integrations, provide observability architecture guidance, troubleshoot platform and pipeline issues, run QBRs to demonstrate ROI, and advocate customer needs across product and sales teams.

The role involves acting as an operational SME for TRADEcho, ensuring compliance, managing operational risks, leading DevOps engineering, and mentoring other engineers. You will own CI/CD pipelines and automate infrastructure provisioning.

The Network Engineer will own production operations of Kubernetes platforms, improve monitoring, support incident response, and collaborate with cross-functional teams on networking solutions.

The Lead DevOps Engineer will automate infrastructure, lead CI/CD pipeline design, manage Kubernetes workloads, and mentor a DevOps team while ensuring high system reliability.

The Senior Data Platform Engineer will architect and build a scalable data platform, enabling teams to manage data with self-serve capabilities using modern tools. Responsibilities include developing microservices, leading technical initiatives, and promoting data governance and observability, collaborating with diverse stakeholders, and mentoring team members.

The AI Engineer will design and build full-stack applications, optimize AI interfaces, and collaborate on integrating AI technologies into enterprise solutions.

As a Software Engineer in the Core AI team, you will design and operate AI model serving infrastructure, build centralised servers, and improve developer experiences through secure, scalable platforms.

As an Engineering Manager, you will lead the Zable App team, balancing hands-on technical leadership with strategic management to ensure technical excellence and efficient delivery across platforms.

The Senior Software Engineer will lead engineering initiatives, resolve technical bottlenecks, support team development, and maintain system reliability for ad integrations.

Join Miro's Messaging team as a Senior Backend Engineer to design scalable notification systems, ensuring reliability and performance while collaborating with product teams.

As a Front Office Quantitative Developer, you will enhance quant technology for algorithmic trading, collaborating with traders and quants to support 24/7 strategies.

Develop and enhance core technology for systematic trading, including front-office systems and automation of trading strategies. Collaborate with traders and quants.

The Full Stack Engineer will design and deliver frontend medical services, maintain existing systems, and engage in collaborative development in a microservices architecture.

The Java Developer will design, build, and optimize medical services, collaborating with product owners and employing best software practices. Involvement with cloud technologies and integration testing is expected, alongside maintaining and enhancing existing services in a microservices architecture.

The Staff AI Engineer will build, deploy, and maintain AI applications, manage data pipelines, and lead technical designs while mentoring engineers.

As a Senior Machine Learning Scientist, you'll improve customer outcomes through automated decisioning using ML and statistical modeling, focusing on credit risk modeling and collaborating with cross-functional teams.