26 to 50 of 889 GCP Jobs in the UK

multiple programming languages such as Python, JavaScript, or similar. Extensive experience writing well-tested code. Good knowledge of cloud platforms (e.g., AWS, Azure, GCP) and infrastructure as code Experience with CI/CD pipelines and automated testing frameworks. Experience with various architecture patterns eg microservices and event-driven. Experience with ...

Python , and microservices (additional languagaes are a benefit). Strong knowledge of Agile , TDD , and DevOps methodologies. Proficiency with cloud platforms (AWS, Azure, or GCP) and Infrastructure as Code. Experience with CI/CD, containerization (Docker, Kubernetes), and automated testing. Proven ability to lead and inspire engineering teams. Excellent communication ...

Python frameworks such as Django, Flask, or FastAPI. Experience with SQL and NoSQL databases (e.g., PostgreSQL, MongoDB). Familiarity with cloud platforms (AWS, GCP, or Azure). Experience with containerization tools (Docker, Kubernetes is a plus). Strong problem-solving skills and attention to detail. Excellent communication and teamwork skills. ...

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 … skilled GCP DevOps Engineer to architect and maintain cloud-native infrastructure that supports high-performance AI systems. This is 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) . ...

ingestion and transformation, and event-driven (Pub/Sub) architectures . This role focuses on building secure, scalable identity and access workflows across Google Cloud Platform, integrating identity services with custom APIs, Pub/Sub pipelines, and cloud-native applications. You will collaborate closely with tech leads, Cloud Security, DevOps ...

Models, LLM, Data preprocessing, REST API, Microservices architecture, MLOps, CI/CD for ML, Power-BI, Docker, Kubernetes, AI Ethics, Cloud Platforms, AWS, Google Cloud Platform, SQL, NoSQL, DevOps, Financial services, Regulatory environments Contract Type: Hybrid/Bedford Daily Rate: £600-£650 (via Umbrella) 9 months initial contract ...

reliable and scalable back-end systems with an object-oriented language. Cloud-native technologies: Experience in architecting and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker), infrastructure-as-code software (e.g., Terraform), and observability platforms (e.g., Datadog or Grafana). Strong ownership mindset ...

software architecture. Hands-on expertise with Java, Spring Boot , and microservices. Strong understanding of Agile and DevOps practices. Familiarity with cloud platforms (AWS, Azure, GCP) and Infrastructure as Code. Experience with CI/CD, containerisation (Docker, Kubernetes), and automated testing. Excellent communication and stakeholder engagement skills. Desirable: Experience in consulting ...

proficiency in one or more programming languages (e.g., Python, Java, JavaScript) and experience with software architecture patterns. Experience with cloud platforms (e.g., AWS, Azure, GCP) and infrastructure as code. Familiarity with CI/CD pipelines, automated testing, and modern software development practices. Knowledge of technologies such as microservices, containerisation (Docker ...

RabbitMQ, MQTT, or similar) Experience with container orchestration and service containerisation (Kubernetes, Docker) Built and deployed services on any major cloud providers' services (Azure, GCP, AWS) AI-Native development: use AI tools such as CoPilot or Cursor a collaborator and accelerator of development. Nice to Have: Experience ...

Desirable: NoSQL database technologies (MongoDB, Cosmos) Docker workflows Container management systems (Kubernetes/Docker Swarm) Knowledge of Cloud solutions (AWS/Azure/Google Cloud Platform) Knowledge of scripting languages (Bash and PowerShell) Administration of Windows and Linux servers About Us Subsidised Onsite Parking. Free fruit, barista bar and juice ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...

language models. Strong grounding in ML concepts — supervised, unsupervised, and reinforcement learning. Familiarity with cloud AI/ML services (Azure Cognitive Services, AWS SageMaker, GCP Vertex AI). Experience deploying and monitoring AI workloads in CI/CD environments (Jenkins, Docker, Kubernetes, AWS). Ability to design data pipelines, APIs ...