Top AWS Jobs in London

Build and operate Neo4j Aura’s Product Analytics Platform, including its Analytics API, event ingestion infrastructure, schemas, and integration contracts. Make architectural decisions for reliability and scalability, guide product teams through adoption, document designs through RFCs, and collaborate with Product Management and downstream data pipeline teams. The role focuses primarily on backend Go development, with some TypeScript or JavaScript and exposure to event-driven systems, observability, cloud platforms, and analytics tooling.

Design, build, and operate cloud-native backend services in Go for Neo4j Aura IAM. Develop custom Kubernetes operators/controllers, drive platform architecture, and implement secure service-to-service authentication (JWT, mTLS, SPIFFE/SPIRE). Collaborate with product, infrastructure, and security teams and produce clear technical documentation.

Leads Intent HQ’s global partnerships and alliances ecosystem, owning partner strategy, quota-carrying revenue, pipeline, deal execution, and commercial program design. Manages relationships with global systems integrators, hyperscalers, technology alliances, and value-added resellers. Develops reseller, referral, white-label, co-sell, and joint-marketing programs while partnering with Sales Operations, Deal Desk, Legal, Product, Delivery, and Customer Success to operationalize agreements and generate revenue.

Design, build, automate, and operate cloud-native network infrastructure to ensure reliability, performance, and observability. Drive test-driven infrastructure changes, support office networking, participate in on-call rotations, incident escalations, code/config reviews, and produce documentation and playbooks for the engineering organization.

The Account Executive will own the full enterprise sales cycle for cloud data security and data risk management solutions across UK&I. Responsibilities include territory planning, prospecting, forecasting, executive engagement, solution positioning, proof-of-value delivery, negotiation, closing, and partner development. The role requires collaboration with Sales Engineering, Customer Success, Product, Marketing, and executive teams, with approximately 50% travel.

Leads Oracle Data and AI consulting engagements across strategy, architecture, implementation, and deployment. Designs scalable data platforms on OCI, develops AI and generative AI solutions using Oracle services, and provides technical leadership to delivery teams. Works with clients to translate business requirements into solutions, supports architecture and proposals, and leads workstreams, mentoring, and business development activities.

Leads complex enterprise cyber investigations and incident response from detection through recovery. Conducts host, network, cloud, identity, and SaaS investigations; performs threat hunting and compromise assessments; develops containment and remediation strategies; briefs executives and boards; partners with legal, compliance, privacy, and audit teams; improves security capabilities through lessons learned and AI-assisted workflows; and participates in 24/7 on-call coverage.

Lead architecture and hands-on development of backend and API platforms supporting ecommerce, loyalty, clienteling, and customer personalization. Build scalable Node.js and TypeScript services, integrations, microservices, and event-driven systems across commerce, payments, fulfillment, CRM, analytics, and digital experience platforms. Own API governance, security, observability, DevOps automation, and cloud infrastructure while mentoring engineers and shaping technical standards and roadmaps.

Build, operate, and improve Azure-focused cloud infrastructure supporting software development, testing, and production. Develop Infrastructure-as-Code, maintain CI/CD pipelines, manage containerized workloads, implement observability, troubleshoot incidents, improve security and reliability, and automate deployment workflows. Collaborate with engineering teams to deliver scalable, cost-efficient platforms.

Leads data science strategy and advanced analytics across drug development programs. Develops statistical, AI, and machine learning models using multimodal clinical and omics data; guides biomarker discovery, precision medicine, trial analysis, and evidence generation. Establishes reproducible pipelines and data quality standards using Python, R, SQL, and cloud platforms. Manages and mentors data scientists while influencing clinical, statistical, and senior leadership decisions.

Design and scale advanced analytics, statistical, machine learning, and AI solutions for Life Sciences customers across Europe. Integrate Veeva Data Cloud with healthcare datasets, build HCP precision-engagement models, translate technical insights into business value, collaborate with cross-functional teams, and document methodologies, architectures, and validation processes.

Leads end-to-end network verification and performance testing across cellular, WiFi, broadband, IP, and AWS-connected environments. Configures testbeds, executes functional, regression, interoperability, resiliency, and performance tests, analyzes traffic and logs, troubleshoots Layer 2–7 issues, performs root-cause analysis, and documents defects and test results. Develops automation using Python or Bash and integrates network verification into CI/CD workflows while collaborating with engineering, DevOps, infrastructure, and network operations teams.

Leads a security engineering team responsible for defining and delivering the security roadmap, designing secure cloud services and platforms, and implementing security tooling. The role combines people management, technical leadership, roadmap and product strategy contributions, design reviews, code reviews, hands-on engineering, recruitment, process improvement, and engineer development. Candidates need experience managing product-aligned engineering teams and securing modern cloud-native technology stacks.

Provides technical leadership for the Marketing and Commercial Data engineering capability. The role owns technical direction, architecture, engineering standards, platform evolution, operational health, technical risk, and cross-team dependencies. It guides migration toward Salesforce Marketing Cloud Next and Data 360 while maintaining existing platforms. Responsibilities include mentoring engineers, supporting complex technical decisions and incidents, partnering with product and business stakeholders, and ensuring secure, resilient, scalable, maintainable systems.

Leads Hyve’s enterprise Data and AI strategy, platform, semantic model, governance, analytics, reporting, self-service, and responsible AI adoption. Manages an 8–10-person multidisciplinary team across data engineering, analytics, and AI; rationalizes reporting; establishes scalable cloud data architecture; delivers generative and agentic AI use cases; and connects data products to commercial value. The role also oversees roadmap planning, budgets, partners, executive stakeholder engagement, organizational change, data literacy, and operational governance.

Develop and maintain production data science models for attribution, marketing mix modelling, incrementality testing, and brand impact measurement. Lead projects end to end, select modelling approaches, debug unfamiliar codebases, apply AI tooling, collaborate with QA, communicate technical findings to clients, and mentor junior colleagues. The role requires strong Python, SQL, machine learning, production engineering, stakeholder communication, and independent ownership.

Leads design and implementation of scalable full-stack features, secure REST APIs, and production software. Responsibilities include incident response, on-call support, security compliance, technical debt reduction, code reviews, testing, architecture best practices, and mentoring. The role requires strong Python, Django, PostgreSQL, React, API development, and application security expertise, with a hybrid London work arrangement.

Lead strategic enterprise customers as a technical Customer Success Manager, owning customer health, revenue realization, technical guidance, escalation management, account plans, executive reviews, and cross-functional collaboration to drive adoption and growth of MongoDB Atlas.

Build and operate digital and data products across complex client environments. Provide hands-on platform, DevOps, cloud, infrastructure, CI/CD, security, observability, and solution-design expertise. Mentor engineers, improve engineering standards, influence technology strategy, and advise senior client stakeholders. Lead or support multiple technology teams, promote continuous delivery and lean practices, and contribute to architectural governance and technology roadmaps.

Own the paid media data domain end to end, including ingestion, user-level modeling, data marts, semantic definitions, reverse ETL, reliability, alerting, and incident response. Lead and mentor data engineers, establish technical standards, shape the roadmap, collaborate with platform and business teams, and remain hands-on in SQL and Python. Build production pipelines using dbt, Dagster, cloud warehouses, and related tooling while supporting analytics, machine learning, and data science use cases.

Build and operate scalable public-cloud platforms supporting participant websites, high-volume health and genetic data processing, de-identification, and secure sharing with Trusted Research Environments. Responsibilities include infrastructure as code, GitOps, CI/CD, Kubernetes, distributed systems, cloud security, ETL tooling, production support, troubleshooting, and defining engineering practices in a growing team.

Build and operate scalable cloud platforms supporting websites, high-volume health and genetic data pipelines, and Trusted Research Environments. Responsibilities include infrastructure-as-code, GitOps, Kubernetes, production troubleshooting, platform improvements, service integration, architectural planning, incident reviews, code reviews, testing, coaching, and on-call support. The role partners with product and engineering teams to deliver reliable, secure systems at scale.

Build and deploy AI-powered solutions directly with clients and internal delivery teams. Responsibilities include scoping ambiguous problems, designing LLM and retrieval workflows, developing scalable backend and infrastructure systems, optimizing operational workflows, translating messy data into technical architectures, iterating with stakeholders, and creating reusable deployment tooling. The role also involves client communication, end-to-end project ownership, customer on-call support, travel for client engagements, and hybrid office work.

Own and develop production systems supporting AI-powered customer experience, including support agents, ticketing, billing workflows, reporting, QA, monitoring, releases, guardrails, and knowledge management. Build TypeScript and Node.js services on AWS, manage AI vendor integrations, create test suites and evaluations, and coordinate improvements across Product, Engineering, Education, Analytics, and community teams.

Leads the Provisioning engineering team building and expanding a cloud-native platform that creates and manages Kubernetes-based development and test environments. Responsibilities include technical design, coding, code reviews, platform strategy, data-driven impact measurement, stakeholder collaboration, engineering best practices, recruitment, process development, and mentoring engineers.