Top AWS Jobs in London

Own the full lifecycle of machine learning features, including research, experimentation, training, deployment, monitoring, and production optimization. Build ML infrastructure for payment routing, establish reliable MLOps practices, partner with product, data, engineering, and customers, mentor engineers, and guide technical priorities. Apply statistical thinking, A/B testing, pragmatic model evaluation, and reinforcement learning concepts in a remote-first environment.

Own the full lifecycle of machine learning features, including research, experimentation, training, deployment, monitoring, and production infrastructure. Build smart payment-routing models and MLOps practices, partner with product, data, engineering, and customers, evaluate outcomes statistically, mentor engineers, and help define ML technical direction and reliable development processes.

Architects and operates highly available Linux infrastructure and core IT services across on-premises and cloud environments. Develops infrastructure-as-code and automation with Terraform, Ansible, Git, Python, and shell scripting; implements secure configuration, patching, and deployment pipelines; administers enterprise storage arrays; and supports networking, virtualization, Kubernetes, compliance, and on-call operations. Acts as a technical subject matter expert, maintains documentation and runbooks, and mentors junior engineers.

Develop and maintain secure, responsive web applications for front-to-back trading technology. Responsibilities include architecture, coding, testing, documentation, production support, requirements gathering, and legacy-platform migration to the cloud. The role emphasizes C# .NET or React, modern DevOps and CI/CD practices, testing, scalability, security, and maintainability. The developer will collaborate with platform engineers, business users, and agile delivery teams in a regulated financial-services environment.

Designs and leads application and cloud architectures for highly scalable financial services systems. Responsibilities include AWS infrastructure design, cloud cost optimization, CI/CD support, quality and security requirements, API and data modeling, production issue resolution, proof-of-concept development, governance, and technical leadership. The role partners with architects, engineers, product owners, business analysts, infrastructure teams, and senior leadership while establishing architectural standards and mentoring technical staff.

Designs and builds end-to-end automation solutions for Lilly’s global Finance organization. Responsibilities include solution design, programming, architecture documentation, testing, UAT support, validation, defect resolution, risk communication, QA, audits, and platform migrations. The role uses Python, PySpark, TypeScript, PostgreSQL, AWS, Microsoft Fabric, SAP, APIs, and emerging AI technologies while partnering with analysts, business teams, and technology stakeholders.

Leads the technical direction of data engineering, owning scalable pipelines, warehouse architecture, data models, ELT transformations, quality monitoring, and platform reliability. Defines engineering standards, reviews designs and code, drives CI/CD and observability, resolves complex technical issues, and mentors engineers. Collaborates with analytics, reporting, data science, and platform teams to translate requirements into performant, cost-effective solutions while contributing to warehouse modernization and technical planning.

Leads Cloudscaler’s Applied AI business unit, owning go-to-market offerings, customer relationships, pre-sales, partner strategy, thought leadership, commercial performance, and P&L growth. Provides technical oversight, builds and manages the AI practice, develops reusable accelerators, establishes delivery standards, and enables AI adoption across the company. The role combines applied AI technical leadership, consulting, business development, team building, and strategic decision-making.

Build and scale Thought Machine’s cloud-agnostic infrastructure platform for global banking software. Responsibilities include developing orchestration and automation tools, designing resilient architectures and disaster recovery systems, improving observability, and optimizing databases and event-streaming platforms. The role requires production infrastructure engineering with Python or Golang, Kubernetes and Docker expertise, and experience extending tools such as Prometheus, OpenTelemetry, and Grafana.

Develop and maintain a Python-based SaaS platform for project, data, and annotation management. Collaborate with data and platform engineers to build efficient data-handling processes and work with stakeholders to define and validate software features. The role supports machine learning and data science teams developing connected surgical technology, using production software engineering, cloud infrastructure, DevOps practices, and iterative development methods.

Design, build and support cloud-native, microservice back-end applications using JVM languages. Deliver end-to-end solutions, write comprehensive tests, manage production incidents, and apply enterprise-authorized AI-assisted development tools while following secure and responsible AI practices.

Build and migrate enterprise software services to Jamf’s platform using Kotlin, Spring Boot, REST APIs, microservices, and AWS. Responsibilities include designing features, independently delivering high-quality software, communicating technical concepts, solving customer problems, and collaborating across technical and product teams. The role also involves mentoring engineers, supporting testing and quality assurance, and adapting within an agile platform migration environment.

Leads complex software engineering initiatives and provides technical guidance while designing, implementing, and managing AWS cloud infrastructure. Develops CI/CD pipelines, supports containerized platforms, monitors system reliability, troubleshoots issues, and applies DevOps best practices. Collaborates with cross-functional teams to define infrastructure needs, improve processes, and deliver secure, high-performing technology solutions.

Design, develop, deploy, and monitor machine learning and AI models, including predictive models, NLP, computer vision, and generative AI solutions. Analyze and transform large datasets, build scalable data pipelines, automate ML workflows, evaluate model performance, and integrate models into production. Collaborate with technical and business stakeholders to deliver actionable insights and continuously improve AI products.

Own Spiko’s end-to-end security strategy across applications, infrastructure, cloud, identity, vulnerability management, testing, detection, and incident response. Lead ISO 27001 certification, DORA implementation, security policies, controls, and audit evidence. Support partner security due diligence and help position security as a sales differentiator. Define the security roadmap autonomously and build a strong company-wide security culture.

Lead development of large-scale, real-time and historical market-data applications using KDB/Q. Drive system design, coding, performance optimization, scalability, high availability, and CI/CD automation. Mentor team members, manage delivery, partner with stakeholders and support teams, and help migrate and re-architect systems to AWS while improving operational stability and testing practices.

Lead DevOps Engineer on an agile team supporting low-latency electronic trading, data analytics and quant environments. Provide technical leadership, develop and review production code, manage CI/CD and release activities, automate tooling, monitor capacity, and deliver third-level production support while advocating firmwide engineering practices.

Lead networking platform engineering for cloud-native systems: design resilient, secure networks on GCP/AWS, build and maintain Kubernetes operators (Golang), improve observability/SLOs, troubleshoot production incidents, drive AI-assisted engineering practices, vendor evaluations, and lead engineering communities and agile ceremonies.

Design, build, and deploy scalable ML services combining NLP, CV, and statistical methods. Collaborate with engineers, cloud and SRE teams to productionize models, ensure observability and compliance, and maintain models over time. Communicate results to stakeholders and document processes for regulatory needs.

Design, build, and productionize autonomous and assistive multi-agent AI systems. Implement RAG and semantic search with vector databases, integrate tools/APIs, apply prompt engineering and guardrails, orchestrate microservices workflows, instrument agents for metrics, run evaluations/A-B tests, and mentor teammates.

Lead design, delivery and maintenance of on-prem and cloud market-data distribution systems (real-time, historical, AI/ML use cases). Collaborate with product/stakeholders, provide 3rd-level operational support, validate AI-assisted recommendations, ensure resiliency, security, auditability and strong process controls.

Lead design and delivery of cloud-native data and AIML production systems. Build data engineering, backend, Cloud infra/DevOps and MLOps stacks, produce secure production code, architect microservices and distributed, data-intensive applications, and drive adoption/governance of AI-assisted engineering practices while communicating with stakeholders.

Lead architecture and roadmap for platform engineering; mentor engineers; design and deliver secure, scalable cloud-native infrastructure; ensure production stability (You Build It, You Run It); automate operations and implement DORA/SLIs/SLOs; drive FinOps and performance tuning; adopt and govern agentic AI-enabled engineering workflows with security and validation guardrails; collaborate with product, business, and security stakeholders.

Lead design and delivery of high-performance, real-time data pipelines and analytics for trading. Drive AI-enabled data engineering, mentor engineers, manage global initiatives, and improve SDLC, testing, and operational reliability.

Senior front-end engineer on an agile Equities Sales & Trading team delivering secure, scalable cloud-native applications. Provides technical leadership, writes and reviews production code, drives design decisions, optimizes UI performance for high-frequency data, and advocates firmwide engineering practices and tools.