101 to 125 of 271 Docker Jobs in Yorkshire

with C#/.NET; full-stack experience preferred Strong background in building and scaling distributed, secure systems Solid understanding of design patterns, architecture, and code review practices Experience with Docker, Kubernetes, RESTful APIs, and microservices Proficient with CI/CD pipelines and tooling (e.g. GitHub Actions, CircleCI) Must be eligible for UK National Security Vetting Desirable Skills Experience with AWS More ❯

with C#/.NET; full-stack experience preferred Strong background in building and scaling distributed, secure systems Solid understanding of design patterns, architecture, and code review practices Experience with Docker, Kubernetes, RESTful APIs, and microservices Proficient with CI/CD pipelines and tooling (e.g. GitHub Actions, CircleCI) Must be eligible for UK National Security Vetting Desirable Skills Experience with AWS More ❯

ideally with full-stack capability. Experience leading teams that build secure, scalable distributed systems. Strong knowledge of architecture patterns , system design, and code review best practices. Practical experience with Docker , Kubernetes , and container-based delivery. Proficiency in building REST APIs and microservice architectures. Strong background with CI/CD pipelines (e.g., GitHub Actions, CircleCI). 💡 Bonus Skills That Impress Delivery More ❯

/.NET (full-stack experience welcomed). Architect, build, and deliver secure distributed systems at scale. Guide a team of engineers, mentoring and leading by example. Work across containerization (Docker, Kubernetes), APIs, microservices, and cloud platforms (Azure, AWS, or GCP). Stay engineering-focused — no consulting or sales duties required. ✅ What You’ll Need Deep knowledge of C# and .NET More ❯

/.NET (full-stack experience welcomed). Architect, build, and deliver secure distributed systems at scale. Guide a team of engineers, mentoring and leading by example. Work across containerization (Docker, Kubernetes), APIs, microservices, and cloud platforms (Azure, AWS, or GCP). Stay engineering-focused no consulting or sales duties required. What You ll Need Deep knowledge of C# and .NET More ❯

/.NET (full-stack experience welcomed). Architect, build, and deliver secure distributed systems at scale. Guide a team of engineers, mentoring and leading by example. Work across containerization (Docker, Kubernetes), APIs, microservices, and cloud platforms (Azure, AWS, or GCP). Stay engineering-focused - no consulting or sales duties required. What You'll Need Deep knowledge of C# and .NET More ❯

across multiple frameworks, ideally React, Vue or Flutter Cloud experience across multiple platforms with the experience of having created your own build environments and CI/CD pipelines. Containerization (Docker/Kubernetes) Familiarity with data design, handling and security Unit/Integration testing experience 6+ years of commercial experience in Software Engineer roles Please note - this is a UK based More ❯

solutioning. Desirable/Nice to Have: Familiarity with GDS (Government Digital Services) guidelines and assessment processes AWS Solutions Architect – Professional or Associate certification Experience with DevOps, CI/CD, Docker/Kubernetes, and infrastructure-as-code tools (Terraform, CloudFormation) Experience with hybrid/multi-cloud solutions More ❯

solutioning. Desirable/Nice to Have: Familiarity with GDS (Government Digital Services) guidelines and assessment processes AWS Solutions Architect – Professional or Associate certification Experience with DevOps, CI/CD, Docker/Kubernetes, and infrastructure-as-code tools (Terraform, CloudFormation) Experience with hybrid/multi-cloud solutions #J-18808-Ljbffr More ❯

Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools More ❯

Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools More ❯

Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools More ❯

Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools More ❯

Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools More ❯

Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools More ❯

Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for ML, reproducibility. Experience with Docker and container orchestration (e.g., Kubernetes). Preferred Skills: Experience with feature stores (e.g., Feast, Tecton). Knowledge of distributed training (e.g., Horovod, distributed PyTorch). Familiarity with big data tools More ❯

reliable and scalable systems with an object-oriented programming language. Cloud-native technologies: Experience in deploying to 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). Curiosity: A hunger to learn and grow your skills. Problem solving: Strong analytical problem-solving skills More ❯

in C#, .Net, with full-stack experience. Experience leading engineering teams building distributed, secure systems at scale. Strong understanding of design practices, architecture, and code reviews. Experience with containerization (Docker, Kubernetes). Knowledge of RESTful APIs and microservices. Experience with CI/CD tools (Github Actions, CircleCI). Preferred Skills: Experience with cloud platforms (AWS, Azure, GCP). Knowledge of More ❯

cloud experience valued) Experience with LLM deployment strategies - both managed services (Bedrock, OpenAI) and self-hosted solutions Understanding of vector databases, embedding systems, and retrieval architectures Technical Expertise: Containerisation (Docker) and orchestration platforms (Kubernetes, ECS, or equivalent) Database design across SQL and NoSQL systems API design, microservices architecture, and distributed systems Cloud infrastructure management and infrastructure-as-code AI/ More ❯

cloud experience valued) Experience with LLM deployment strategies - both managed services (Bedrock, OpenAI) and self-hosted solutions Understanding of vector databases, embedding systems, and retrieval architectures Technical Expertise: Containerisation (Docker) and orchestration platforms (Kubernetes, ECS, or equivalent) Database design across SQL and NoSQL systems API design, microservices architecture, and distributed systems Cloud infrastructure management and infrastructure-as-code AI/ More ❯

cloud experience valued) Experience with LLM deployment strategies - both managed services (Bedrock, OpenAI) and self-hosted solutions Understanding of vector databases, embedding systems, and retrieval architectures Technical Expertise: Containerisation (Docker) and orchestration platforms (Kubernetes, ECS, or equivalent) Database design across SQL and NoSQL systems API design, microservices architecture, and distributed systems Cloud infrastructure management and infrastructure-as-code AI/ More ❯

solutioning. Desirable/Nice to Have: Familiarity with GDS (Government Digital Services) guidelines and assessment processes AWS Solutions Architect – Professional or Associate certification Experience with DevOps, CI/CD, Docker/Kubernetes, and infrastructure-as-code tools (Terraform, CloudFormation) Experience with hybrid/multi-cloud solutions Seniority level Seniority level Mid-Senior level Employment type Employment type Full-time Job More ❯

messaging Worked with defining data models and interacting with databases Built software that includes user facing web applications. Skills we’d love to see/Amazing Extras: Experience with Docker, Kubernetes or other serverless application delivery platforms Used GIT, Jenkins, GitHub or Azure DevOps Worked Generative AI and large language models such as Azure AI Services or Chat GPT. Used More ❯

Python & Bash. Knowledge of Linux-based operating systems. Experience with Amazon Web Services cloud platform or another cloud platform. Proven work experience with containerization and orchestration tools such as Docker, Airflow, Prefect and Kubernetes. Knowledge of cybersecurity best practices. Excellent communication and collaboration skills. Ability to work effectively in a fast-paced and dynamic environment. Self-discipline and delivery focused. More ❯

experience leading engineering teams building distributed systems and secure products at scale. Have a solid understanding of design practices, system architecture and conducting code reviews. Experience using containerization technologies (Docker, Kubernetes etc) Experience with RESTful APIs and microservices best practices. Extensive experience with CI/CD tooling (Github Actions, CircleCI etc) Skills we’d love to see/Amazing Extras More ❯