Top AWS Jobs in London

Design, operate, and scale large distributed systems for telemetry processing. Build automation, use AI tooling to reduce toil, ensure availability and disaster recovery, participate in on-call incident response, troubleshoot production AWS/Kubernetes environments, and collaborate with application teams to meet SLOs/SLAs.

Lead and scale Monte Carlo's partner ecosystem across EMEA by recruiting, enabling, and managing cloud, SI, and consultancy partners; build joint GTM plays; drive partner-sourced pipeline and co-marketing; run field events; and cultivate executive relationships to expand market presence and accelerate revenue.

Build and maintain ultra-high-scale data platforms and pipelines (petabyte scale). Write fault-tolerant Java/Spark code, design low-latency query capabilities, improve performance and stability, participate in technical reviews, and enable customers/internal teams to query and extract analytics from event data.

Design, build, and operate highly scalable real-time streaming microservices and data pipelines (Java/Python/Go) using Kafka, Flink/Spark on Kubernetes across multi-cloud and on-prem. Own design, deployment, monitoring, observability, and on-call support while improving platform reliability and developer experience.

Design, implement, and operate discoverability and search features for the AISOAR marketplace. Lead end-to-end technical implementations, ensure high availability and security, troubleshoot platform issues, collaborate with customers and security partners, use observability tools, drive platform improvements, and participate in monthly on-call rotation.

Design and implement a scalable cloud detection engine that processes billions of events across multi-cloud environments. Build custom query languages, event orchestration and correlation systems, collaborate with security researchers to convert detections into production features, lead backend engineering, mentor teammates, and improve architecture, performance, and reliability using Go, cloud platforms, Kafka, Cassandra, Docker and related technologies.

Design, architect, and develop scalable Go-based microservices and REST APIs for threat detection, case management, and incident response. Lead system design, own technical initiatives, mentor engineers, integrate AI/LLM capabilities, operate cloud-native services on Docker/Kubernetes and cloud platforms, participate in on-call rotation, and drive reliability and architectural improvements.

Build and scale cloud-native backend services for a global detection-engine platform. Design high-performance, resilient distributed systems, collaborate across teams, mentor engineers, and drive testing, CI, and AI-enhanced detection workflows at internet scale.

Build, operate, and scale CrowdStrike's global backbone and hybrid cloud networks. Design and implement IP and optical solutions, drive capacity planning, evaluate technologies, automate with IaC and CI/CD, support cloud networking, lead projects from ideation to implementation, and participate in 24x7 on-call rotation.

Lead and mentor data science teams to design, develop, and deploy ML and AI solutions (including GenAI/LLMs). Align technical outcomes with business goals, drive MLOps and model governance, and deliver scalable production systems.

The Senior Data Scientist will unify technical vision, develop and deploy ML models, and enhance AI strategy across teams. Responsibilities include collaboration, ownership of projects, and maximizing value through AI and data science techniques.

Design, prototype, implement and optimize predictive models for sporting outcomes. Collaborate in an agile, multidisciplinary team, apply probability and machine learning methods, deploy models, and mentor junior colleagues.

Lead and manage a team of data scientists to design, build and deploy predictive sports models. Oversee algorithm development (probability, Monte Carlo, ML), mentor staff, collaborate with engineers and product managers, and ensure continuous delivery and high-performance, production-ready model implementations across multiple sports.

Lead and transform a global Product Security and Security Operations program. Embed security into SDLC, own threat detection, incident response, vulnerability management, cloud and application security, offensive testing, tooling consolidation, and 24/7 coverage. Build risk-backed visibility for executives, develop distributed teams, manage vendors/MSSP, and drive security culture and automation across engineering.

Lead client engagements while developing analytics strategies. Coach teams, analyze data, and create impactful business recommendations.

Design, build, test, and operate backend services and REST APIs (Java/Kotlin, Spring Boot) for high-volume payin workflows. Work on payment orchestration, card pay-ins, PostgreSQL data modeling and SQL optimization, Kafka-based event processing, automated testing, code reviews, on-call rotations, and cross-team delivery while ensuring security and regulatory compliance.

Own end-to-end regulatory reporting datasets: map regulations to internal data, build and automate pipelines, implement data quality controls, create clear visualisations, investigate discrepancies, and partner with cross-functional stakeholders to ensure accurate, auditable reporting.

Own and deliver end-to-end solutions across services, APIs, UI surfaces, and event flows. Design reliable production systems, handle monitoring and incidents, debug distributed systems, collaborate with product and cross-functional teams, and improve quality through tests, observability, and simpler designs.

Serve as a subject-matter expert in telemetry pipelines and observability, supporting enterprise sales and customer success. Lead technical proofs-of-concept, advise on pipeline design and routing (OpenTelemetry, Fluentd/Bit, Logstash), optimize costs and analytics, build ROI/value cases, enable field teams, and drive platform adoption and pipeline development across sales, engineering, and marketing.

Lead a platform engineering squad to deliver scalable, cloud-native solutions. Drive technical vision, engineering standards, incident response, and adoption of AI-assisted development and automation. Coach engineers, manage delivery roadmaps, ensure operational stability, and align technical work with business and regulatory requirements.

As a Software Engineer at Legora, you will build and implement features for a web platform, maintaining code quality and mentoring junior colleagues.

Lead projects using cloud technologies for business solutions, ensuring timely delivery, client satisfaction, and mentoring team members while leveraging advanced analytics and technology platforms.

Develop and maintain scalable cloud ecosystems using Golang and Python, enhancing backend microservices and collaborating within a fast-paced team.

As a Backend Engineer, you'll build and improve technology for small businesses, focusing on developing reliable code, collaborating on projects, participating in code reviews, and enhancing operational efficiency.

As an Applied AI Engineer, you will build AI applications for public sector clients, create and evaluate datasets, and collaborate with teams to address challenges using AI solutions.