126 to 150 of 1,104 GCP Jobs in the UK excluding London

systems (eg. Kafka/Pulsar, 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 in frontend development (eg. Javascript, Typescript, React.js) Worked More ❯

systems (eg. Kafka/Pulsar, 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 in frontend development (eg. Javascript, Typescript, React.js) Worked More ❯

systems (eg. Kafka/Pulsar, 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 in frontend development (eg. Javascript, Typescript, React.js) Worked More ❯

proficient in using AI-coding assistants (like Cloude Code) to substantially optimise delivery cycles. Experience with data engineering, APIs, and developing full-stack solutions in cloud platforms (AWS, Azure, GCP). Familiarity with procurement systems, defence contracting, or government tech is a strong plus. Ability to work independently and drive innovation in ambiguous environments. Excellent problem-solving, communication, and stakeholder More ❯

proficient in using AI-coding assistants (like Cloude Code) to substantially optimise delivery cycles. Experience with data engineering, APIs, and developing full-stack solutions in cloud platforms (AWS, Azure, GCP). Familiarity with procurement systems, defence contracting, or government tech is a strong plus. Ability to work independently and drive innovation in ambiguous environments. Excellent problem-solving, communication, and stakeholder More ❯

proficient in using AI-coding assistants (like Cloude Code) to substantially optimise delivery cycles. Experience with data engineering, APIs, and developing full-stack solutions in cloud platforms (AWS, Azure, GCP). Familiarity with procurement systems, defence contracting, or government tech is a strong plus. Ability to work independently and drive innovation in ambiguous environments. Excellent problem-solving, communication, and stakeholder More ❯

proficient in using AI-coding assistants (like Cloude Code) to substantially optimise delivery cycles. Experience with data engineering, APIs, and developing full-stack solutions in cloud platforms (AWS, Azure, GCP). Familiarity with procurement systems, defence contracting, or government tech is a strong plus. Ability to work independently and drive innovation in ambiguous environments. Excellent problem-solving, communication, and stakeholder More ❯

frameworks such as PyTorch, TensorFlow, or Scikit-learn. Knowledge of probability, statistics, and common ML techniques. Hands-on experience with at least one major cloud platform (AWS, Azure, or GCP). Proficiency with containers, Docker, and Kubernetes. Strong communication skills with the ability to work across technical and non-technical teams. Comfortable working in a high-growth, fast-paced environment. More ❯

implementation. Vector databases and similarity search systems. Graph databases (ArangoDB, Neo4j, Neptune) and property graph modelling. Data engineering: ETL pipelines, document processing, schema design for AI applications. Cloud platforms (GCP preferred, AWS/Azure also relevant) and containerisation (Docker). Observability and monitoring for LLM applications (tracing, metrics, cost tracking). Secure coding practices for regulated industries and sensitive data More ❯

implementation. Vector databases and similarity search systems. Graph databases (ArangoDB, Neo4j, Neptune) and property graph modelling. Data engineering: ETL pipelines, document processing, schema design for AI applications. Cloud platforms (GCP preferred, AWS/Azure also relevant) and containerisation (Docker). Observability and monitoring for LLM applications (tracing, metrics, cost tracking). Secure coding practices for regulated industries and sensitive data More ❯

implementation. Vector databases and similarity search systems. Graph databases (ArangoDB, Neo4j, Neptune) and property graph modelling. Data engineering: ETL pipelines, document processing, schema design for AI applications. Cloud platforms (GCP preferred, AWS/Azure also relevant) and containerisation (Docker). Observability and monitoring for LLM applications (tracing, metrics, cost tracking). Secure coding practices for regulated industries and sensitive data More ❯

enough to adapt across others. Essential Skills: Proven experience leading software engineering teams Deep expertise in one major stack (Java, Python, Node.js, etc.) Strong cloud knowledge (AWS, Azure, or GCP) Agile delivery experience and a pragmatic problem-solving mindset Bonus Points For: Test-driven development and continuous delivery practices Experience with enterprise integration patterns Interest in AI tools and emerging More ❯

etc.). 2. Hands-on experience with OpenShift Virtualization and Kubernetes. 3. Proficiency in scripting languages (e.g., Bash, Python) for automation tasks. 4. Knowledge of cloud platforms (AWS, Azure, GCP) and hybrid cloud environments. 5. Familiarity with CI/CD tools (Jenkins, GitLab, ArgoCD, etc.). 6. Strong understanding of networking, storage, and virtualization concepts. 7. Experience with version control More ❯

etc.). 2. Hands-on experience with OpenShift Virtualization and Kubernetes. 3. Proficiency in scripting languages (e.g., Bash, Python) for automation tasks. 4. Knowledge of cloud platforms (AWS, Azure, GCP) and hybrid cloud environments. 5. Familiarity with CI/CD tools (Jenkins, GitLab, ArgoCD, etc.). 6. Strong understanding of networking, storage, and virtualization concepts. 7. Experience with version control More ❯

deployment. Connect AI models to backend systems and user interfaces for seamless operation. Monitor and evaluate models, tackling bias and improving explainability. Deploy AI solutions using cloud services (AWS, GCP, Azure) and Python. Optimise performance, reduce latency, and implement best-practice CI/CD workflows. Document processes, architectures, and results for regulatory and internal review. Skills & Experience We’re Looking More ❯

deployment. Connect AI models to backend systems and user interfaces for seamless operation. Monitor and evaluate models, tackling bias and improving explainability. Deploy AI solutions using cloud services (AWS, GCP, Azure) and Python. Optimise performance, reduce latency, and implement best-practice CI/CD workflows. Document processes, architectures, and results for regulatory and internal review. Skills & Experience We’re Looking More ❯

Experienced in securing work through RFI/RFPs, bids, and presentations across public and private sectors. Skilled in data science platforms (e.g. Databricks, AzureML) and cloud services (AWS, Azure, GCP), with knowledge of tools like Terraform. Experienced in deploying solutions using Docker, Kubernetes, CI/CD tools. To be Considered: Please either apply by clicking online or emailing me directly More ❯

enable agents that learn and improve autonomously. Deploy at Scale: Integrate your agents into enterprise ecosystems (ERP, CRM, financial platforms) and deploy on cloud platforms like Azure, AWS, or GCP with robust observability. Collaborate & Influence: Partner with data scientists, product managers, and stakeholders to translate complex business needs into intelligent, autonomous workflows. Champion Ethical AI: Ensure your agents comply with More ❯

communication skills and a team-oriented attitude Nice to Have (But Not Required): Internship, university project, or research involving machine learning or data science. Experience with cloud platforms (AWS, GCP, or Azure) Knowledge of software engineering best practices, version control (Git), or CI/CD pipelines Understanding of deep learning, NLP, or computer vision Familiarity with deployment tools like Docker More ❯

communication skills and a team-oriented attitude Nice to Have (But Not Required): Internship, university project, or research involving machine learning or data science. Experience with cloud platforms (AWS, GCP, or Azure) Knowledge of software engineering best practices, version control (Git), or CI/CD pipelines Understanding of deep learning, NLP, or computer vision Familiarity with deployment tools like Docker More ❯

communication skills and a team-oriented attitude Nice to Have (But Not Required): Internship, university project, or research involving machine learning or data science. Experience with cloud platforms (AWS, GCP, or Azure) Knowledge of software engineering best practices, version control (Git), or CI/CD pipelines Understanding of deep learning, NLP, or computer vision Familiarity with deployment tools like Docker More ❯

communication skills and a team-oriented attitude Nice to Have (But Not Required): Internship, university project, or research involving machine learning or data science. Experience with cloud platforms (AWS, GCP, or Azure) Knowledge of software engineering best practices, version control (Git), or CI/CD pipelines Understanding of deep learning, NLP, or computer vision Familiarity with deployment tools like Docker More ❯

communication skills and a team-oriented attitude Nice to Have (But Not Required): Internship, university project, or research involving machine learning or data science. Experience with cloud platforms (AWS, GCP, or Azure) Knowledge of software engineering best practices, version control (Git), or CI/CD pipelines Understanding of deep learning, NLP, or computer vision Familiarity with deployment tools like Docker More ❯

communication skills and a team-oriented attitude Nice to Have (But Not Required): Internship, university project, or research involving machine learning or data science. Experience with cloud platforms (AWS, GCP, or Azure) Knowledge of software engineering best practices, version control (Git), or CI/CD pipelines Understanding of deep learning, NLP, or computer vision Familiarity with deployment tools like Docker More ❯

statistical modelling 📈 Strong problem-solving and analytical mindset 🗣 Excellent communication skills and a genuine passion for learning Nice to Have: 💾 Experience with SQL, data pipelines , or cloud platforms ( AWS, GCP, or Azure ) 📊 Familiarity with MLOps tools or model deployment practices 📚 Exposure to NLP, computer vision, or generative AI projects (academic or personal) 💻 Previous internship or project experience in AI, data More ❯