Top AWS Jobs in London

Develop and productionize machine learning systems that personalize Spotify’s subscription journey, improving conversion, retention, payment experiences, and subscriber growth. Lead ML initiatives from requirements through deployment and impact measurement, build scalable data pipelines and models, maintain reliable and observable systems, collaborate cross-functionally, and contribute to experimentation, optimization, and reusable ML capabilities.

Own customer-facing Data and AI technical engagements from discovery through proof-of-value and delivery handover. Lead workshops, architecture design, demonstrations, proofs of concept, proposals, and technical evaluations. Partner with Revenue, Engineering, Product, Marketing, and cloud or SI partners to support account strategy, co-selling, and go-to-market activities. Advise enterprise customers on modern data platforms, AI solutions, governance, ROI, and technical implementation while creating reusable reference architectures and demo assets.

Design, develop, test, deploy, and support secure, scalable full-stack applications using C#, .NET, React, and Next.js. Manage Azure infrastructure, Docker containers, Kubernetes orchestration, GitOps deployments, CI/CD pipelines, observability, and PostgreSQL or SQL Server databases. Collaborate with product and engineering teams, contribute to architecture and code reviews, mentor colleagues, champion test-driven development, and improve application reliability and delivery automation.

Own the Martech strategy and operations connecting first-party data with CRM, performance marketing, advertising platforms, and customer data systems. Implement and optimise data flows, audience segmentation, attribution tracking, marketing technology, and campaign processes. Translate marketing needs into technical briefs, coordinate stakeholders and vendors, conduct UAT, support GDPR compliance, document data practices, and implement governed AI use cases across marketing workflows.

Set technical direction across Motorway’s engineering organization, evolve architecture and engineering standards, improve reliability, observability, security, and incident practices, and lead AWS and AI-for-software-engineering adoption. The role develops staff engineers, evaluates platforms commercially and technically, manages AWS relationships, and represents Motorway at conferences and industry events.

Own software products end to end, from problem definition and design through production operation. Build across front-end, back-end, services, and APIs; use and review AI coding agents; maintain tests and safeguards; monitor real-world usage; contribute to reliable cloud systems and on-call support. Mentor teammates, improve engineering conventions, and collaborate closely with product, design, and users in a complex energy domain.

Lead the development and adoption of MLOps infrastructure, tooling, and standards across Trainline. Productionise AI and ML products, automate deployments and service modernisation, improve monitoring, governance, security, and cost tracking, and support platform migrations. Evaluate technical approaches, guide architecture, communicate decisions, and mentor engineers while partnering with ML teams to deliver reliable customer-facing and internal AI systems.

Lead the design, implementation, operation, and optimization of enterprise Privileged Access Management and broader IAM/IGA solutions. Responsibilities include onboarding privileged access, supporting CyberArk or comparable PAM platforms, managing EPM solutions, partnering with cloud and infrastructure teams, addressing security risks, supporting audits and compliance reviews, and providing global operational support. The role requires expertise across Active Directory, LDAP, Azure or AWS, cloud identity services, and business-critical environments.

Designs and delivers AI-enabled platform capabilities, workflows, agents, and enterprise products. Owns solutions end to end across frontend, backend, AI, integrations, deployment, monitoring, and continuous improvement. Collaborates with data scientists, AI engineers, and platform engineers to productionize research and build scalable, observable, secure systems. Requires strong TypeScript, JavaScript, frontend, backend, database, API, architecture, testing, and CI/CD skills, with AI, MLOps, cloud, and financial services experience preferred.

Designs, builds, and optimizes AWS cloud infrastructure and automation for a mission-critical genomics organization. Responsibilities include maintaining Terraform and Ansible IaC, developing GitLab CI/CD pipelines, creating reusable platform templates, enforcing cloud governance, monitoring performance, troubleshooting issues, and supporting engineering enablement. The role also contributes to cloud strategy, security, cost management, reliability, and mentoring application teams in a blended working environment.

Leads engineering for a new business unit, setting technical direction, architecture, engineering practices, and delivery standards. Builds and scales the engineering team, remains hands-on with coding and reviews, partners with Product and Design on roadmap decisions, and develops future leaders. Owns quality, security, scalability, observability, incident response, stakeholder communication, hiring, and collaboration with Platform and Data teams.

Design, build, and operate scalable batch and near-real-time data pipelines, ETL/ELT workflows, integrations, data models, and curated data products. Own solutions through deployment, monitoring, troubleshooting, and continuous improvement while implementing testing, governance, security, observability, and CI/CD practices. Provide technical leadership, mentor engineers, collaborate with cross-functional teams, and enable trusted, AI-ready player data for analytics and business transformation.

Build and evaluate machine learning models, clean and transform data with Python and SQL, perform statistical analysis, create visualizations, and support experiments and product metrics. Collaborate with engineering and data teams to productionize and monitor models, identify drift, prototype generative AI solutions, and follow responsible AI, version control, testing, and documentation practices.

Design, implement, benchmark, and optimize machine learning and computer vision models for low-latency edge and cloud deployment. Develop real-time surgical video processing pipelines, improve network architectures, write high-quality production code, and collaborate with machine learning, platform, embedded software, and research teams. The role also involves researching state-of-the-art optimization methods and communicating results across technical and business stakeholders.

Design and deliver scalable search and customer-facing features using OpenSearch, AWS, React, GraphQL, and modern backend technologies. Maintain AWS infrastructure, develop clean and tested code, support service integrations, and collaborate on AI/ML-driven capabilities. The role includes technical mentoring, engineering leadership, system design, cross-functional collaboration, and championing best practices across the organization.

Own and evolve a multi-account AWS platform defined with Terraform and Terramate. Build reusable infrastructure modules, manage ECS services, IAM, CI/CD, databases, observability, security tooling, and third-party integrations. Implement ISO 27001 controls, support penetration testing, administer access management, investigate incidents, improve developer productivity, and control cloud costs. The role requires hands-on production infrastructure experience, strong security and compliance practices, and collaboration through infrastructure reviews and PR-driven changes.

Lead the design, deployment, and scaling of machine learning and generative AI systems. Guide end-to-end model development, architecture, production reliability, MLOps, and engineering excellence. Mentor engineers, shape technical roadmaps, collaborate cross-functionally, and drive organization-wide AI adoption. The role combines hands-on technical leadership with people management in a fast-paced startup environment.

Leads end-to-end cloud solution architecture across Azure and AWS, covering migrations, modernization, landing zones, platforms, security, governance, and cloud-native environments. Owns architecture for customer opportunities, bids, RFPs, and delivery engagements; produces design documentation, leads workshops and reviews, assures implementation quality, and manages risks. Partners with engineering and delivery teams, develops reusable standards and blueprints, and mentors other architects.

Design, deploy, operate, and support production-grade Generative AI solutions across EMEA. Responsibilities include developing RAG and agentic architectures, evaluating models and platforms, collaborating with business and technology stakeholders, managing governance and risk, providing L1–L3 support, and ensuring responsible AI, security, privacy, and regulatory compliance in a financial services environment.

Lead the design, delivery, governance, support, and continuous improvement of enterprise AI solutions across EMEA. Build generative AI, RAG, and agentic systems; evaluate platforms and models; establish engineering standards; manage SDLC, security, privacy, and responsible AI controls; track outcomes and ROI; and provide operational support. Partner with business stakeholders, mentor engineers, promote reusable architectures, and drive technology adoption within a regulated financial-services environment.

Own Cisco’s technical relationship with Amazon, leading consultative sales, solution design, demonstrations, technical validation, and complex networking architecture strategies. Advise Amazon leaders on networking, UCS, security, observability, automation, hybrid cloud, and connectivity. Collaborate with Cisco teams and partners, influence technical decisions, drive competitive displacement and revenue growth, resolve escalations, and shape strategic infrastructure initiatives. The role requires extensive technical sales or network architecture experience and travel up to 50%.

Lead end-to-end business analysis and discovery for Salesforce consulting programs. Facilitate workshops, define processes, requirements, user stories, acceptance criteria, KPIs, and traceability matrices. Collaborate with architects and developers through testing, UAT, and go-live; manage stakeholder decisions, risks, and dependencies. Contribute to pre-sales, consulting methods, and analyst mentoring.

Owns enterprise IT infrastructure and end-user computing across on-premises, cloud, identity, networking, endpoints, and segmented environments. Responsibilities include Azure/AWS administration, systems hardening, patching, vulnerability remediation, endpoint and identity management, backups, disaster recovery, audit evidence, incident response, asset lifecycle, documentation, automation, and advanced technical support. The role independently drives infrastructure modernization, security compliance, operational resilience, and controlled access for a security-sensitive entity.

Leads technical strategy, solution architecture, delivery, and product development for Altana’s UK policy and national security vertical. Owns capture and pre-sales technical content, customer deployments, security and accreditation obligations, support processes, staffing, and technical team development. Partners with commercial leadership, Platform Operations, Engineering, Product, and Design to deliver SaaS and PaaS solutions in secured and regulated environments.

Lead the design, development, and deployment of scalable, production-grade machine learning systems. Define ML deployment standards, make architectural decisions, collaborate with technical and commercial teams, advise clients, and mentor engineers. The role requires expertise across the ML lifecycle, software engineering, cloud infrastructure, containerization, orchestration, and responsible AI delivery.