Top AWS Jobs in London

Lead the architectural evolution of an AI platform from monolithic to distributed systems. Design agent-ready services, write production Python, build distributed compute and workflow orchestration, and own CI/CD, testing, deployment, observability, reliability, and scaling. Mentor engineers, establish technical standards, guide cross-team decisions, collaborate with stakeholders, and support hiring. The role requires deep distributed systems, Kubernetes, AWS, workflow orchestration, data processing, security, and production reliability expertise.

Integrate security into software delivery and infrastructure workflows across AWS and GCP. Build scanning into CI/CD pipelines, maintain security guardrails, secure containerized workloads, implement least-privilege access and secrets management, and support compliance with SC TRM and BNM RMiT. Improve monitoring, vulnerability reporting, incident readiness, and secure delivery practices while collaborating with platform and engineering teams using multiple programming languages.

Leads end-to-end architecture for enterprise AI platforms and data transformation programs. Responsibilities include solution design, delivery governance, technical risk management, team leadership, client advisory, architecture workshops, business development, bid support, and practice growth. Designs cloud, data, AI, orchestration, agentic, evaluation, guardrail, observability, and responsible-AI solutions for production-scale deployments.

Lead and support live broadcast delivery for major sporting events across on-premise and cloud environments, primarily AWS. Monitor, troubleshoot, and optimize video workflows; coordinate timelines, requirements, and stakeholders; develop Python automation; support reporting and knowledge sharing; and travel internationally for event deployments. The role includes irregular evening and weekend hours during live events.

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.

Manage and maintain compliance with security and privacy frameworks (ISO 27001, SOC 2, HIPAA, PCI DSS). Coordinate audits, drive remediation, improve controls and evidence management, support security questionnaires for deal cycles, and design compliance training while partnering across teams to integrate controls into the SDLC.

The Senior Software Engineer will develop and maintain Lua business logic for ad serving, ensuring performance and reliability while collaborating with product teams on feature delivery.

The role involves designing and building cloud-native applications using Java and Spring Boot, focusing on scalable microservices for financial institutions while leading agile practices.

Build and scale internal systems and tooling for a large social gaming platform. Responsibilities include collaborating cross-functionally, delivering software in an agile environment, troubleshooting systems, managing risk through DevOps and testing, improving development processes, and maintaining secure, reliable, scalable services. The role requires frontend and backend development, including React, WordPress, Python, and Golang, plus expertise in microservices, event-driven systems, and distributed computing.

Lead technical response to security events across Twilio's global cloud infrastructure: triage, contain, remediate, document incidents, build runbooks and automations, drive post-incident improvements, participate in on-call rotation and RCAs, and collaborate with R&D to scale threat mitigation and incident response capabilities.

Develops technical strategy and integrated security solutions for managed service provider partners. Responsibilities include designing solutions, delivering demos and enablement, supporting technical sales, engaging partner engineering and SOC teams, building managed security offerings, serving as a cloud security evangelist, and advising on cloud, AI, DevSecOps, MDR, DSPM, and multi-cloud security. Travel is required up to 40% of the time.

Deploy and configure cybersecurity platforms for customers across Google SecOps and Microsoft Sentinel. Responsibilities include onboarding log sources, configuring connectors and ingestion pipelines, deploying SIEM/SOAR content, troubleshooting technical issues, training customers, documenting configurations, and managing multiple concurrent deployments.

Leads technology strategy, roadmap, governance, and delivery for digital marketing, content, web, analytics, and AI capabilities across Gilead’s Ex-US Commercial organization. Partners with Commercial, Medical, Legal, Compliance, and IT stakeholders to deliver scalable solutions using Salesforce Marketing Cloud, Veeva Vault PromoMats, AWS, Databricks, and other platforms. Owns product lifecycles, vendor management, demand planning, analytics, AI enablement, and compliant digital transformation.

Lead customer engagements building and productionizing AI and generative AI applications on Databricks. Responsibilities include architecture, technical delivery, client advisory, team leadership, workshops, MLOps, production pipelines, stakeholder communication, and technical enablement. The role requires strong Python, cloud, MLflow, Databricks, PySpark, SQL, Delta Lake, governance, LLM, and modern AI framework expertise in a consulting environment.

Own and evolve Chip’s data platform architecture, including scalable pipelines, medallion architecture, data modeling, governance, security, and self-service enablement. Establish engineering standards, apply Databricks and Terraform best practices, optimize performance, and mentor data engineers. The role requires hands-on expertise in Databricks, Python, PySpark, SQL, databases, Git, infrastructure as code, and PII governance, with opportunities to re-architect the platform in a regulated fintech environment.

Designs and deploys production computer vision solutions using Ultralytics YOLO. Responsibilities include technical discovery, architecture design, Python prototyping, model training and optimization, benchmarking, deployment across cloud and edge environments, customer demos, workshops, proof-of-concepts, stakeholder management, and creating reusable documentation and integrations. The role partners with Sales, Customer Success, Product, and Engineering while owning technical outcomes throughout the customer lifecycle.

Design and build backend systems for AI agent orchestration, tool execution, workflow management, memory, and state handling. Develop scalable APIs and reliable infrastructure for distributed AI workflows, improve platform reliability and observability, and partner with product, research, and engineering teams to deliver agent capabilities. Own technical initiatives from architecture through production, maintain software quality through testing and continuous delivery, and mentor engineers on backend and distributed-systems practices.

Develop and scale Lightning AI’s backend platform using Go, spanning APIs, infrastructure, billing, security, and integrations. Own features end to end, design reliable and scalable systems, improve architecture and performance, maintain software quality and continuous delivery, reduce technical debt, and mentor engineers. Collaborate with engineering, product, and design teams in a fast-changing SaaS environment.

Design and scale backend systems for AI agent orchestration, distributed workflows, experiment management, platform APIs, and developer tooling. Build reliable cloud-native infrastructure, improve observability and performance, partner across engineering and research teams, maintain software quality through testing and continuous delivery, and mentor engineers on distributed systems and backend best practices.

Support customer trust, security assurance, and compliance programs by responding to security questionnaires, maintaining documentation, coordinating evidence collection, and supporting audit readiness. The role translates technical controls into customer-facing responses, collaborates with security, engineering, legal, and go-to-market teams, and improves GRC workflows across SOC 2, ISO 27001, ISO 42001, EU AI Act, UK Cyber Essentials, and GDPR requirements.

Lead technical customer-facing GenAI engagements for EMEA digital-native and startup customers. Design and productionize LLM solutions including RAG, agents, fine-tuning, evaluation, safety, and MLOps on Databricks. Build proofs of concept and reference implementations, advise customer roadmaps, partner with Product and Engineering, mentor field teams, and represent Databricks through technical content and executive briefings.

Lead technical pre-sales engagements for Databricks, demoing Spark and data/AI solutions, building architectures, authoring reference materials, and collaborating with account teams to design and deliver customised proofs-of-concept and workshops.

Leads innovation within the Enterprise Change Management Office by identifying AI and automation opportunities, designing future-state operating models, developing prototypes and production solutions, and driving enterprise adoption. Oversees innovation frameworks, policies, controls, roadmaps, integrations, feedback loops, and measurable value realization while partnering with business, technology, risk, architecture, engineering, and organizational change teams.

Provide technical customer support by triaging tickets, investigating logs, reproducing bugs, writing queries, and escalating issues to Engineering. Maintain SLAs, participate in on-call coverage, create runbooks and knowledge-base content, support integrations, communicate during incidents, and identify recurring customer pain. Partner with Engineering, Product, Customer Success, and Account Management while improving AI-assisted support tooling.

Lead enterprise application transformation engagements from discovery through implementation and transition. Advise CIOs, CTOs, and senior stakeholders on modernization, migration, technical debt remediation, cloud transformation, portfolio rationalization, business cases, and roadmaps. Lead multidisciplinary teams, governance, risk management, delivery oversight, business change, user adoption, and operating-model development while aligning technology investments with business outcomes.