1 to 25 of 338 GCP Jobs in London

Hedge Fund PERM GCP Cloud Security Engineer - GCP, AWS, Azure, Python, Bash, IAM, Terraform, Automation Cloud Security Engineer The successful candidate will be a subject … matter expert with hands-on experience in a wide range of cloud technologies, tools and methodologies. The role is suited for an experienced Cloud Engineer with focus in Google Cloud Platform, the candidate must have proven understanding in enterprise security and will focus on building toolsets and processes. Principal Responsibilities Contribute to the vision, strategy, and drive execution for integrated … security controls across Software-as-a-Service (SaaS), Platform-as-a-Service (PaaS), Infrastructure-as-a-Service (IaaS) and for Google Cloud Platform (GCP) efforts. Able to demonstrate clear understanding of current risks and threats to Cloud infrastructure and/or IT infrastructures at technical and managerial levels. Ability to conduct Red Team security testing tasks in GCP to continuously More ❯

supplier list for this position.KeywordsCloud Engineer, Full Stack Developer, Data Engineer, Java Developer, Node.js, React Developer, Kubernetes, Docker, Red Hat OpenShift, CI/CD, GitHub, ArgoCD, PostgreSQL, AWS, Azure, GCP, DevOps, Agile, Power BI, Data Pipelines, Microservices, Hybrid Working, Security Clearance, Leadership, Management. More ❯

GCP DevOps Engineer - AI Infrastructure (Financial Services) Location: London Contract Type: Full-time/Permanent 2 days required at Office and 3 from home per week £(Apply online only) DOE Join a forward-thinking financial services firm leveraging AI to transform decision-making and customer experiences. We're seeking a skilled GCP DevOps Engineer to architect and maintain cloud-native … a hands-on technical role with strategic impact across infrastructure, automation, and security. Key Responsibilities Infrastructure & Cloud Engineering Design, build, and manage scalable, resilient infrastructure on Google Cloud Platform (GCP) . Implement Infrastructure as Code (IaC) using Terraform to ensure consistent and secure deployments. Utilize GCP services such as Compute Engine , Cloud Run , Cloud Functions , BigQuery , and Kubernetes to support … up monitoring and alerting systems using Cloud Monitoring , Cloud Logging , Prometheus Troubleshoot infrastructure issues and ensure minimal downtime for critical AI services. Required Skills Strong hands-on experience with GCP services : Compute Engine, Kubernetes, Cloud Storage, BigQuery, Cloud Run. Proficient in scripting with Python or Bash . Deep understanding of Docker and Kubernetes for containerization and orchestration. Expertise in CI More ❯

learning, and AI frameworks such as Langchain, Semantic Kernel agent SDK and related libraries. Designs and delivers AI solutions on leading cloud platforms (Amazon Web Services, Microsoft Azure, Google Cloud Platform), leveraging native AI/ML services and cloud-native architectures. Develops and manages robust data pipelines, big data technologies (e.g., Spark, Kafka), and data management practices for feature stores More ❯

Prior experience working with or for a Global Systems Integrator (GSI). Proven experience in pre-sales, solution architecture, or consulting roles. Strong understanding of cloud platforms (AWS, Azure, GCP), DevOps, and microservices. Hands-on experience with observability tools, APM, log analytics, and infrastructure monitoring. Proficiency in scripting or programming languages (e.g., Java, Python, JavaScript). Certifications in Dynatrace, AWS More ❯

management, and inter-system messaging (e.g., Kafka, RabbitMQ, or similar). Practical experience with Docker and Kubernetes for containerization and orchestration. Working knowledge of cloud platforms (Azure, AWS, or GCP) and concepts of managing cloud resources efficiently. Experience with Infrastructure as Code (IaC) using tools such as Terraform. Strong understanding of CI/CD pipelines, automated testing, and continuous delivery More ❯

the following engineering disciplines : Cloud Engineering Data Engineering (not building pipelines but designing and building the framework) DevOps MLOps/LLMOps Often work with the following technologies : Azure, AWS, GCP Airflow, dbt, Databricks, Snowflake, etc. GitHub, Azure DevOps and related developer tooling and CI/CD platforms, Terraform or other Infra-as-Code MLflow, AzureML or similar for MLOps; LangSmith More ❯

candidate will meet all of the following essential criteria: Demonstrable experience in designing large scale cloud migration projects/programmes with open source and commercial software within AWS, Azure, GCP or hybrid Experience in operating within a multi-disciplined team and clearly communicating complex technology solutions to technical and non-technical people Experience designing event processing and async messaging architectures More ❯

coder with Full Stack Development experience including: Proficient coding experience using Python Experience with SQL and backend development (Node.js with SQL is a plus) Proficiency in Clout Platfoms: Ideally GCP, but AWS or Azure also welcome DevOps Engineering experience understancing basic principals and tools such as: Kubernetes Terraform (infrastructure as code) CI/CD pipelines and automated deployment processes Benefits More ❯

that will help you excel: 10-15 years of backend or platform engineering experience. Proven experience building and deploying microservices in production within a cloud environment (AWS, Azure, or GCP). Expertise in Go, Node.js, or Java, with deep understanding of distributed systems and API design. Experience integrating or leveraging AI/ML models or services within production systems. Familiarity More ❯

About the role Skills: PostgreSQL, Go, React, Google Cloud, TypeScript Languages - Go, Typescript, Postgresql Frameworks/Infra - Encore, Next.js, Vercel, GCP, Rende About you We are looking for a startup-focused and experienced software engineer, who is keen on solving the real-world problems in an industry ripe for innovation. You excellent communication skills and think from first principles. You More ❯

platforms like Kubernetes or Docker Swarm. Understanding of containerized environments and their integration into CI/CD pipelines • Cloud Platforms: Familiarity with major cloud platforms like AWS, Azure, or GCP; understanding of cloud-specific services and how to integrate them into CI/CD processes • Monitoring and Logging: Knowledge of monitoring and logging tools such as Prometheus, Grafana, ELK Stack More ❯

platforms like Kubernetes or Docker Swarm. Understanding of containerized environments and their integration into CI/CD pipelines • Cloud Platforms: Familiarity with major cloud platforms like AWS, Azure, or GCP; understanding of cloud-specific services and how to integrate them into CI/CD processes • Monitoring and Logging: Knowledge of monitoring and logging tools such as Prometheus, Grafana, ELK Stack More ❯

data effectively. Familiarity with distributed systems concepts such as event sourcing, resilience patterns, and asynchronous communication. Experience with containerised development (Docker) and deploying cloud-native applications (Azure, AWS, or GCP). Strong understanding of DevOps concepts: CI/CD pipelines, automated testing, infrastructure-as-code patterns. Proficiency in unit, integration, and end-to-end testing using modern TypeScript testing tools. More ❯

broader programme and client objectives. About You Professional knowledge and experience Essential Proven experience in data engineering, data integration and data modelling Expertise with cloud platforms (e.g. AWS, Azure, GCP) Expertise with modern cloud data platforms (e.g. Microsoft Fabric, Databricks) Expertise with multiple data analytics tools (e.g. Power BI) Deep understanding of data wareho using concepts, ETL/ELT pipelines More ❯

Exposure to Kubernetes, containerised environments, and Helm-based deployments. Understanding of CI/CD pipelines (GitLab CI) and infrastructure-as-code workflows. Experience working in cloud-native environments (AWS, GCP, or Azure) and awareness of security-first design. Comfort working with financial datasets, trade logs, or analytics dashboards. Experience handling sensitive or regulated data, ideally in financial or crypto contexts. More ❯

build an end-to-end pipeline consuming other data products Basic qualifications: Extensive experience conducting Bankend Development using Python. Concurrency and Asyn exp Demonstrated experience using FastAPI Cloud Experience - GCP Essential SQL Docker Containerization Unit testing experience - TDD or Test Suit ML or AI experience would be desriable. Experience within Life Sceiences or Pharma Sector If you are available and More ❯

don't ask that you have experience in all of this, but if you do, that's great! Java, which makes up the majority of our backend codebase AWS & GCP - we're cloud-native Microservice based architecture Kubernetes (EKS) TeamCity for CI/CD (with multiple production releases per day) Terraform and Grafana Our Interview process Interviewing is a two More ❯

microservice-based architectures using domain driven design (DDD). CQRS and Event Sourcing patterns * Kubernetes * Knowledge/Certification in Spring framework. * Experience in cloud technologies AWS/Azure/GCP Please apply for the job if you fit the above criteria. More ❯

Deep expertise in Python Application Development (FastAPI), with a strong SQL capability. Hands-on experience building data pipelines, APIs and backend services. Solid understanding of cloud platforms (Azure/GCP) and Bash scripting. Advanced Docker knowledge, including storage, volumes and permissions. Strong grounding in software engineering principles, version control and CI/CD. Ability to review and improve others' code More ❯

of algorithms, data structures and cloud concepts. Experience contributing to solution design and familiarity with architectural patterns/frameworks. Proven delivery of serverless pipelines in Azure/AWS/GCP (Azure highly desirable). Experience building data transformation pipelines using SQL and NoSQL databases. Hands-on ownership of CI/CD (Jenkins/Azure DevOps/GitHub Actions) and MLOps More ❯

grounding in algorithms and software engineering* Experience designing ML/AI solutions and working with common architecture patterns* Background in serverless data/ML pipelines (Azure preferred, AWS/GCP welcome)* Proficiency in SQL and NoSQL data stores* Broad understanding of machine learning methods (regression, tree-based models, clustering, deep learning, attention models, transformers, vector representations)* Ability to explain technical More ❯

architecture discussions and supporting more junior engineers Working closely with product, data, and design teams to bring new ideas to life Building and scaling cloud-based systems (AWS/GCP/Azure) Driving quality across the codebase through testing, automation, and CI/CD About You 5+ years of hands-on Python engineering experience Strong background in backend development, APIs More ❯

case management, decisioning capabilities, and the PEGA rules engine. Nice to have: Active Security Clearance (SC) Proven experience working within Agile delivery frameworks Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) Strong understanding of DevOps practices, including CI/CD pipelines and automated testing tools for PEGA Background in regulated sectors such as Banking, Insurance, or More ❯

case management, decisioning capabilities, and the PEGA rules engine. Nice to have: Active Security Clearance (SC) Proven experience working within Agile delivery frameworks Familiarity with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes) Strong understanding of DevOps practices, including CI/CD pipelines and automated testing tools for PEGA Background in regulated sectors such as Banking, Insurance, or More ❯