Top AWS Jobs in London

Design, build, and operate scalable, secure cloud infrastructure and CI/CD pipelines. Manage Kubernetes environments, implement IaC (Terraform), improve observability, troubleshoot production issues, support security/compliance, and mentor junior engineers to optimize platform reliability and cost.

Design, build, fine-tune, and deploy production-grade AI and ML systems (LLMs, RAG). Develop scalable APIs, integrate AI into business systems, monitor model performance, and collaborate with cross-functional teams.

Lead and scale the company's automation infrastructure and products while remaining hands-on. Design orchestration, monitoring, and resilient event/queue-driven workflows; integrate n8n and multiple SaaS tools; build AI/LLM production systems with Claude/OpenAI; ship client-facing and internal products; set engineering best practices, CI/CD, and observability; hire, mentor, and manage an automation engineering team and partner with the founder on technical strategy toward CTO growth.

Serve as the technical bridge between product and sales: lead technical discovery, demos, and POCs; build custom integrations and demos; translate customer feedback into product requirements; create technical sales collateral; troubleshoot pre-sales and onboarding issues; monitor market and competitor trends to inform positioning.

Design, build, deploy, and optimize AI/ML models and pipelines (including LLMs and RAG). Integrate models into production, work with cross-functional teams, ensure monitoring and compliance, and contribute to scalable AI systems and automation.

Manage post-sale relationships for a designated EMEA account base, driving renewals, upsell/cross-sell, onboarding, adoption, and customer advocacy. Collaborate with sales, solutions architects, and internal teams, report on customer health and opportunities (SFDC), and act as trusted advisor to maximize retention and revenue.

Serve as principal technical authority for enterprise cloud architectures, designing and demonstrating secure, scalable software supply chains. Lead deep technical discovery, architect integrations using Terraform and Helm, advise on Cloud AI/LLM/vector DB security, drive complex PoCs with Fortune 500 accounts, and mentor SEs while influencing product roadmap.

Design and deliver enterprise architecture and deployment blueprints for Cohesity solutions. Lead migration and transition efforts, assess risks, size and document solutions, validate deployments in the field, train partners/customers, and provide product feedback to engineering and product teams.

Design, deploy, and maintain reliable cloud-native infrastructure using Terraform, Azure, and Kubernetes. Troubleshoot incidents, lead incident resolution and post‑mortems, improve CI/CD and monitoring, reduce toil, manage security risks, and lead client and supplier engagements to expand SRE practices.

Design, build and maintain cloud-based data engineering solutions and knowledge graphs using Python and AWS. Implement high-quality data pipelines, optimize performance, manage containerised workloads with Docker, and maintain CI/CD, automated testing, and collaborative enterprise data platform integrations.

Own cloud architecture intelligence and cost optimization: analyze cloud spend, identify inefficiencies, build dashboards, enforce governance, partner with engineering/finance to drive cost-conscious design and operations.

The Sr. Solution Architect will drive customer success by providing cloud solutions, pre-sales support, technical advisory, and relationship management, ensuring scalability and efficiency in cloud environments.

The Senior Technical Architect will lead the architectural strategy for a global SaaS platform, mentor engineers, and integrate AI capabilities, while collaborating with Product and Engineering teams.

Lead the development of backend services for government clients, focusing on high availability and scalability, while collaborating in agile teams and maintaining deployment pipelines.

The Lead Data Architect will shape data strategy, design secure data architectures on AWS, mentor teams, and ensure compliance with regulations.

Lead Kraken's Data Platform team focused on real-time infrastructure for data systems, managing team dynamics, architecture design, and promoting AI automation.

As a Lead Machine Learning Engineer, you will set technical direction for ML projects, design scalable systems, mentor engineers, and drive innovation. You'll ensure successful project outcomes while balancing trade-offs and guiding team priorities.

Design, deploy, and govern enterprise-scale data architectures and platforms to support analytics and AI. Define modeling standards, integration pipelines, data quality, lineage, and security. Lead technical direction, mentor engineers, evaluate AI tooling, and support proofs of concept and solution roadmaps that enable generative AI and RAG solutions.

Own and operate Databricks-based data platform production support, build and migrate ETL/ELT pipelines to Databricks across Azure/AWS, optimize compute and performance, enforce Delta Lake architecture and data security, implement observability and CI/CD, support multi-tenant onboarding and on-call incident response, and maintain runbooks and SLA metrics.

Design, build, operate, and improve cloud-native Kubernetes platforms. Maintain cluster health, GitOps, IaC (Terraform), CI/CD, observability, incident response, cost and performance optimisation. Partner with engineering teams, support deployments, reduce technical debt, and for Lead roles own roadmap, mentor engineers, and manage stakeholder priorities.

Build, optimise and stabilise AWS-based data pipelines (S3, Glue, Redshift, Lake Formation). Resolve technical debt, support the Architect on target-state design, collaborate with client engineering teams to transfer knowledge, and deliver production-ready platforms in regulated, high-volume gaming environments.

Validate and automate testing for AWS serverless, event-driven and modernized applications. Design and run functional, integration, contract, performance, resilience and security tests. Build automated test frameworks, integrate with CI/CD, leverage AWS Kiro for AI-assisted test generation and validation, and support migration/regression testing across microservices.

Develop AWS serverless, event-driven cloud-native applications; build streaming data pipelines; modernize legacy systems to microservices and API-first designs; implement CI/CD and Infrastructure as Code (CDK/CloudFormation); ensure monitoring, logging, and system reliability (CloudWatch).

Lead and manage delivery teams to design and deliver low-code solutions (Dynamics 365/Power Platform). Define functional and non-functional architectures, advise customers on technical implications and estimation, own intelligent automation projects, create requirements and user stories, and coach and develop team members while defining standards and sharing knowledge.

The Operations AWS Senior UX Specialist will design and optimize Amazon Connect solutions, enhancing user experiences in contact centre services through effective UX and service design, data-driven optimizations, and collaboration with various teams.