Top AWS Jobs in London

Design, build, and maintain low-latency, high-throughput distributed backend microservices for pricing. Implement caching, design APIs and data models, participate in architecture and code reviews, operate event-driven systems (Kafka/Kinesis), and integrate AI/ML-enabled solutions safely.

Owns the end-to-end architecture of a global hosting capability across public and private clouds. Defines standardized hosting models, datacentre patterns, security controls, risk and trust capabilities, and multi-cloud portability strategies. The role provides technical leadership, architecture governance, roadmap development, AI-enabled platform integration, governance automation, stakeholder management, and mentoring while supporting regulated-market delivery across multiple countries and infrastructure products.

Design and deliver enterprise-grade machine learning systems and AI-powered applications for banking. Build scalable, secure, distributed applications and automated cloud, desktop, and ML pipelines. Apply MLOps practices for versioning, reproducibility, and observability while collaborating with cloud and site reliability engineering teams. Develop reusable libraries and business-critical, data-intensive solutions, aligning machine learning problems with business objectives. The role may include mentoring or people leadership.

Build, review, and ship end-to-end features for Legora’s AI-native legal workspace. The role involves architecting web-platform functionality, owning code quality, security, and development speed, working across frontend and backend technologies, reviewing code, mentoring junior engineers, and driving continuous improvement. Engineers should demonstrate strong judgment, autonomy, pragmatic architecture, and the ability to understand unfamiliar codebases. Infrastructure and integration experience is advantageous.

Build and scale reliable, API-driven global payment systems integrating with banks and payment gateways. Translate requirements into maintainable, tested software; collaborate cross-functionally; resolve performance and usability issues; participate in code reviews; manage technical debt; and support operational health and high service-level availability.

Design, develop, test, and maintain high-volume payment services and REST APIs using Java, Kotlin, Spring Boot, AWS, PostgreSQL, and Kafka. Build payment orchestration and card pay-in systems, optimize performance and scalability, write automated tests, review code, participate in on-call support, and ensure secure handling of financial data and regulatory compliance.

Develop and deploy production AI/ML applications for digital banking, using Python, SQL, cloud platforms, LLM patterns, classical machine learning, and data analysis. Responsibilities span requirements gathering, solution design, prototyping, evaluation, deployment support, monitoring, governance, and iteration. The role collaborates with product, operations, marketing, and technical teams to deliver customer and operational improvements while supporting risk, privacy, and model controls.

Build and scale reliable, API-driven global payment systems integrating banks and payment gateways. Translate product and design requirements into maintainable, tested components; improve performance, accessibility, and usability; contribute to shared libraries and code reviews; and support feature operational health. Collaborate with product, business, operations, design, and backend teams while driving technical decisions, architectural improvements, and engineering practices for large-scale financial infrastructure.

Lead the design and delivery of complex front-end features and shared foundations for Clear Street Studio. Establish architecture, testing, tooling, and code-quality standards; mentor engineers; partner with product, design, and backend teams; and ensure reliability, observability, scalability, performance, and high service-level availability across the platform.

Build and support a high-performance futures and options execution management platform. Responsibilities include translating requirements into tested software, integrating real-time market data and low-latency exchange connectivity, implementing risk controls and trading capabilities, resolving performance and usability issues, participating in code reviews, maintaining shared components, and supporting reliable production operations. The role requires close collaboration with product, trading, design, business, and engineering teams.

Own production system reliability, incident response, observability, automation, and recovery workflows. Build self-healing capabilities, diagnostic tooling, runbooks, and golden-path operational workflows while partnering with platform and engineering teams on CI/CD, infrastructure resilience, SLOs, and reliability improvements. The role combines hands-on production support with development of automation that reduces toil, accelerates recovery, and prevents recurring failures.

The Senior Data Platform Engineer will manage Databricks infrastructure, develop cloud systems, collaborate with teams, and enhance machine learning workflows.

Leads liquidity reporting and regulatory change initiatives within Corporate Treasury Middle Office. Responsibilities include managing regulatory and audit deliverables, resolving reporting issues, improving controls and data quality, developing business requirements, testing data and reports, coordinating technology implementations, analyzing large datasets, and presenting findings to senior stakeholders and regulators. The role uses data and cloud technologies to modernize liquidity reporting and governance.

Manage an engineering team building reusable infrastructure platforms and core distributed systems. Architect highly available services, review designs, plan roadmaps, optimize cloud costs, and enforce deployment standards across AWS and GCP. Lead planning, retrospectives, on-call practices, and reliability initiatives involving SRE, CI/CD, chaos engineering, and incident analysis. Develop engineering strategy, mentor senior engineers, and influence platform decisions across product teams.

Supports CI/CD pipelines, cloud infrastructure provisioning, containerized deployments, automation, monitoring, troubleshooting, and security practices. Collaborates with software developers, testers, and cloud engineers in an agile environment while learning DevOps, DevSecOps, GitOps, and cloud-native engineering. The role also contributes scripts, testing, validation, performance optimization, and continuous improvement across cloud platforms.

Lead analytical data science for Wise’s customer support organization. Measure service quality, diagnose root causes, design metrics, evaluate interventions, and use experiments, causal inference, machine learning, NLP, and LLM techniques to improve customer outcomes. Partner with Product, Design, Operations, and Engineering to guide automation strategy, prioritize opportunities, and influence product and business decisions using customer, conversational, and operational data.

Develop and deploy production AI and machine learning solutions for Markets Operations, including process automation, anomaly detection, document intelligence, workflow optimization, and generative AI. Responsibilities include model development, MLOps, performance monitoring, dataset analysis, stakeholder collaboration, documentation, and continuous improvement of AI-driven business tools.

Lead strategy and delivery for AI and agentic products that automate operational workflows in corporate and investment banking. Identify high-impact use cases, own roadmaps and product requirements, guide cross-functional teams through launch, develop project plans, and align senior stakeholders. The role requires end-to-end AI product management experience, knowledge of LLM architectures and agentic methods, and the ability to connect product execution to measurable business outcomes.

Lead technology risk and controls activities across cybersecurity and business applications. Assess, monitor, and report risks; evaluate controls; identify gaps; recommend mitigation strategies; support regulatory compliance; document issues and action plans; and conduct threat modeling with application teams. The role requires collaboration with senior stakeholders and technology teams, plus knowledge of SDLC, cloud infrastructure, IAM, data protection, application security, resiliency, and vulnerability management.

Designs and supports end-to-end digital asset management and media supply chain workflows, API integrations, metadata and ETL architectures, automations, and AI/ML-enabled operational solutions. Partners with business stakeholders, clients, product, engineering, operations, and vendors to translate requirements into scalable content workflows. Responsibilities include ingest, metadata enrichment, QC, transcoding, delivery, archival, troubleshooting, documentation, platform support, and vendor coordination.

Leads a team building secure, production-grade AI-driven software systems. Responsibilities include software architecture, Java or Python development, AI/ML integration, LLM and generative AI applications, algorithm validation, automated testing, CI/CD, cloud-native development, troubleshooting, and operational reliability. The role also establishes responsible AI practices, validates AI-assisted engineering outputs, mentors engineers, translates business requirements into technical roadmaps, and ensures timely delivery through Agile methodologies.

Senior Solutions Architect in MongoDB’s pre-sales organization, guiding enterprise customers in designing scalable, reliable applications and distributed systems using MongoDB and cloud technologies. Responsibilities include architecture reviews, technical discovery, demonstrations, proofs of value, sizing, documentation, account planning, demand generation, and customer success. The role partners closely with sales teams, advises technical and business stakeholders, mentors colleagues, and travels up to 25%.

Design and ship production software for Navan’s expense platform across backend, web, and AI services. Build APIs, event-driven financial workflows, LLM agents, document extraction, and conversational expense experiences. Improve accuracy, latency, cost, safety, observability, and provider failover while ensuring idempotency, auditability, permissions, and reliable financial-system behavior. Partner with Product and Design, mentor engineers, review code, write technical designs, and support production quality across international expense, payments, policy, and accounting workflows.

Design and develop scalable backend systems for a global expense management platform supporting commerce, payments, issuing, ledgers, automated policies, administrative controls, and accounting integrations. Own features end to end from architecture and implementation through deployment, monitoring, troubleshooting, and operational support. Collaborate with engineering, product, design, and business teams while promoting high standards for scalability, testing, documentation, reliability, and code quality.

Design, build, and operate enterprise-grade, cloud-native data platforms and pipelines for Preqin's Company Intelligence. Provide technical architecture, end-to-end delivery, data governance, observability, and reliability while leading and mentoring a small team and partnering with product and analytics to deliver measurable business value.