Top AWS Jobs in London

Designs and operates scalable data pipelines, warehouse models, and analytics solutions. Builds natural-language data interfaces using GenAI and LLM techniques, optimizes SQL, improves data quality and observability, and supports distributed data platforms on AWS or GCP. Partners with engineering, analytics, product, and business teams while contributing to standards, testing, documentation, code reviews, production support, and incident response.

Develop and improve InstaLILY’s core AI platform, collaborating with product, design, UI/UX, and business teams to deliver reliable customer-focused features. The role includes writing software, testing, supporting CI/CD practices, maintaining technical quality, and staying current with AI and software engineering technologies. Candidates should have 0–2 years of software engineering experience, programming experience in Python and JavaScript, and familiarity with cloud computing or AWS, Azure, or GCP.

Build and operate AWS cloud infrastructure using infrastructure as code, containers, CI/CD pipelines, monitoring, and automation. The role includes optimizing ECS and Fargate workloads, improving CircleCI and GitHub Actions, managing observability with New Relic, participating in incident response, supporting disaster recovery, and applying security practices such as IAM, secrets management, patching, and network segmentation. The engineer will collaborate with product, support, and security teams while maintaining runbooks and operational tooling.

Designs and maintains scalable Ruby on Rails backend services, performant REST APIs, database schemas, and complex business logic. Optimizes PostgreSQL queries, caching, and background jobs while ensuring reliability, security, and code quality. Partners with product and frontend teams, leads system design, mentors engineers, reviews code, owns features through deployment, and resolves production issues. The role also drives engineering standards, technical improvements, testing, and continuous delivery.

Design, build, optimize, and productionize machine learning pipelines, data engineering workflows, tooling, and low-latency Python/C++ systems. Partner with quantitative researchers to turn trading model prototypes into scalable production systems. Responsibilities include architecture design, performance optimization, automated testing, cloud deployment, model serving, and supporting real-time inference for sports betting analytics.

Lead daily IT support operations, guide and coach IT Engineers, resolve escalated technical issues, and improve service quality. Manage support across Windows, macOS, Linux, mobile devices, and office equipment. Oversee onboarding and offboarding, ITSM systems, reporting, documentation, workflow automation, and process optimization. Collaborate with Security and Engineering to maintain reliability and data protection while supporting hybrid offices and preparing for progression into IT management.

Build and maintain shared Python services, frameworks, data pipelines, and APIs powering AI products. Design scalable AWS-based SaaS platforms, data ingestion and processing systems, and integrations with internal and third-party services. Improve platform security, observability, testing, CI/CD, documentation, and monitoring while collaborating with product teams and mentoring engineers.

The Staff Engineer will lead architectural design for researcher operations systems, integrating SaaS components, and managing technical strategy while collaborating across teams.

Build and maintain cloud-native platforms and tools that enable rapid, secure service provisioning. Apply site reliability practices across distributed systems, debug production issues, write maintainable code, and improve architectural patterns. Operate cloud and Kubernetes platforms, automate infrastructure and software delivery through CI/CD, use observability tools, develop Infrastructure as Code modules, document solutions, and support engineering teams adopting reliable operational practices.

Senior Site Reliability Engineer responsible for maintaining and improving production infrastructure supporting cloud-based core banking and payments platforms. Duties include designing resilient systems, disaster recovery, backups, redundancy, capacity planning, automation, observability, on-call support, production maintenance, documentation, and reliability-focused product development. The role also involves mentoring engineers, collaborating with product teams and customers, and managing complex fleet operations across SaaS environments.

Build and maintain reliable infrastructure management tooling for cloud-based banking software. Responsibilities include automating deployments, developing observability and orchestration tools, supporting scalable and highly available services, contributing to disaster recovery and backup strategies, and improving code quality and engineering processes. The role uses Python or Golang and involves cloud platforms, databases, event streaming, container orchestration, and CI/CD systems.

Build and operate high-performance backend systems and distributed services using Elixir and Phoenix. Design declarative infrastructure with Terraform, Terramate, FluxCD, Kubernetes, and Helm; manage AWS cloud workloads, cluster upgrades, GitOps workflows, observability, and databases. Collaborate with a remote engineering team on architecture, product development, debugging, reliability, and customer success.

Lead platform architecture and delivery for enterprise digital transformation programs, designing cloud platforms across Azure, GCP, and AWS. Build Kubernetes, GitOps, IaC, observability, security, networking, and self-service developer platforms. Architect infrastructure for generative AI and agentic systems, guide application modernization, establish governance and guardrails, translate business requirements into technical roadmaps, and mentor multidisciplinary engineering teams and senior stakeholders.

Manage and architect cloud and self-hosted infrastructure for a regulated bank. Responsibilities include operating FoundationDB and Kubernetes, building infrastructure as code, maintaining Bazel and CI/CD systems, improving reliability through multi-region failover and chaos engineering, managing security access and observability, optimizing cloud costs, and supporting hybrid-cloud infrastructure. The role requires strong systems, networking, cloud, programming, and production reliability experience in a high-autonomy startup environment.

Build and maintain scalable data platform solutions supporting analytics and business decision-making. Collaborate with product, analytics, and engineering teams to solve complex problems, improve data reliability, manage infrastructure, and enable fast insights. Responsibilities include developing data-intensive systems, working with cloud platforms and warehouses, applying infrastructure-as-code and CI/CD practices, and balancing scalability, cost, security, and delivery speed.

Leads customer technology transformation initiatives across AI, cloud, data, enterprise architecture, trading technology, and digital workflows. Builds trusted-advisor relationships with senior technology executives, identifies strategic opportunities, supports revenue growth, and guides proofs of concept and platform adoption. Provides customer insights to product and technology teams, leads a technology practice area, develops reusable frameworks, and represents LSEG at industry forums.

Build and operate high-throughput trading data pipelines, analytics engines, time-series models, and analytical databases. Develop internal AI platforms, RAG pipelines, prompt-management tools, and controllable agent systems. Optimize systems for reliability, performance, data quality, reconciliation, monitoring, and cost. Collaborate with quantitative trading teams using financial and cryptocurrency datasets, market data, and trading metrics such as PnL, risk, balances, and trade activity.

Lead application security for the platform by embedding automated controls into the SDLC, conducting security architecture and code reviews, driving threat modeling, triaging vulnerabilities, coordinating remediations, partnering with engineering/product teams, and scaling tooling and AI-assisted workflows to raise security across cloud-native and containerized environments.

As a Senior Software Engineer, you will design and build Palantir's managed Kubernetes products, automating operations across diverse environments. You'll ensure scale, stability, and security while contributing to CNCF tools and improving infrastructure standards.

Design, build, test, and deploy scalable AI services integrated with operational systems. Develop Python services, REST APIs, ETL/data pipelines, IaC, and monitoring; collaborate with AI specialists and operations stakeholders to improve workflows, controls, and production readiness in Markets Operations.

Lead WAM data architecture and cloud transformation engagements: define enterprise data strategies, design canonical WAM data models, architect cloud-native data platforms, integrate core WAM systems, establish data quality and control frameworks, and advise senior stakeholders on technical-to-business translation.

Build, operate, and improve secure, scalable AWS infrastructure for ELN platform services. Responsibilities include infrastructure-as-code, automation, observability, incident response, cloud security, reliability improvements, troubleshooting, peer code reviews, and collaboration with engineering, security, and DevOps teams.

Designs and implements secure, scalable AWS architectures supporting quantitative research and large-scale data analysis. Collaborates with researchers, developers, and data scientists; automates infrastructure deployment and monitoring; optimizes performance, availability, reliability, and cost; troubleshoots complex cloud environments; and promotes AWS best practices across the specialist team.

Lead end-to-end incident response for high-severity security events across cloud environments, perform DFIR investigations, build detection and automation (including AI-assisted) workflows, partner cross-functionally, produce executive communications and RCAs, maintain runbooks/playbooks, and mentor other engineers within a 24/7 global on-call model.

Lead end-to-end technical strategy for customer accounts, design scalable data, AI, streaming, and analytics architectures, and guide production deployments. Serve as a trusted advisor to senior technical stakeholders, drive Databricks adoption and consumption, lead competitive technical wins, coordinate cross-functional resources, and provide product feedback. The role requires strong Python and SQL coding, cloud expertise, distributed data systems knowledge, and excellent communication skills.