13 of 13 Amazon Cognito Jobs in the UK excluding London

microservices , event-driven architecture , and cloud-native development . Strong understanding of SQL and NoSQL databases (PostgreSQL, DynamoDB, Redis). Proficient in AWS cloud services especially Lambda, SQS, S3, Cognito, API Gateway, EventBridge, etc. Hands-on experience with DevOps practices (CI/CD pipelines, Docker, GitHub Actions). Familiarity with frontend tooling such as Vite, ESLint, CSS-in-JS More ❯

but looking for the environment and tech culture to progress further. Experience of Design Systems/Figma in the development process Playwright (or similar testing frameworks like Cypress) Monorepo Cognito SQS Exposure or experience in the use of Design Systems (antd, material-ui) and Figma would be advantageous. Deeper knowledge of accessibility and how it applies to building digital More ❯

efficient and reliable software delivery What You’ll Bring Extensive experience in our modern technology stack which includes React, Node.js and Typescript Experience with the AWS services such as Amazon Cognito, DynamoDB Lambda, S3, Eventbridge, AppSync, API Gateway and SQS Experience using Serverless stack to build and deploy serverless applications into AWS cloud Exceptional communication skills within the More ❯

across the company Requirements Must Haves 3+ years of experience in a DevOps, SRE, or infrastructure-focused engineering role Strong experience with AWS services (EC2, ECS, RDS, S3, IAM, Cognito) Proficiency with infrastructure-as-code (especially AWS CDK, but Terraform or similar also a plus) Hands-on experience with Docker and container orchestration (ECS, EKS, or Kubernetes) Experience setting More ❯

with SQL-based and NoSQL (Document-based) databases. Deep understanding of AWS services and cloud environments. Familiarity with AWS Cloud Development Kit (CDK)and services like Lambda, SQS, S3, Cognito, EventBridge, and more. Experience with DevOps practices, including CI/CD pipelines, Docker, and GitHub Actions. Strong knowledge of security best practices for APIs and data privacy. Proficiency in … diverse audiences. Detail-oriented with a commitment to delivering high-quality, reliable work. Client Tech Stack: Languages : Node.js, TypeScript, React Databases : PostgreSQL, DynamoDB, Redis AWS Services : Lambda, SQS, S3, Cognito, EventBridge, CloudFormation, Fargate, SES, CodeBuild, CodePipeline, CloudFront, API Gateway, and more. What happens next? One of our Recruitment Consultants will be in touch and inform you if youve been More ❯

managing on premise Kubernetes clusters Deep knowledge of Kubeflow or similar systems such as MLflow Proficient in Python and experienced with Linux systems Familiar with AWS services such as Cognito, S3, EC2 and Lambda Experience working with ML frameworks such as PyTorch or Lightning Capable of designing and delivering ML Ops solutions across various platforms Desirable Skills Background in More ❯

managing on premise Kubernetes clusters Deep knowledge of Kubeflow or similar systems such as MLflow Proficient in Python and experienced with Linux systems Familiar with AWS services such as Cognito, S3, EC2 and Lambda Experience working with ML frameworks such as PyTorch or Lightning Capable of designing and delivering ML Ops solutions across various platforms Desirable Skills Background in More ❯

take ownership, but the future of the technical strategy is largely down to you. As it stands the stack includes a TypeScript serverless backend built on AWS Lambda, using Cognito for authentication and RDS for data storage, all orchestrated with the Serverless Framework. A Next.js frontend has been combined with static generation with server-side rendering, and Strapi CMS More ❯

cluster. Excellent knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able More ❯

cluster. Excellent knowledge of Kubeflow and similar systems, e.g. MLflow Good programming ability in Python with familiarity with Linux systems including scripting and system configuration. Experience using AWS, e.g, Cognito, S3, EC2, Lamdas, etc. Experience with ML toolkits, e.g. PyTorch, Lightning, etc., along with a solid understanding of how these fit into ML Ops pipelines and tools. Be able More ❯

in cloud technologies, software and architectural design patterns. Required Qualifications: Bachelor's degree in Computer Science, Electrical Engineering, or a related field. 5+ years of industry experience. Experience with Amazon AWS services such as EKS, S3, SQS, RDS, Cognito, and Lambda. Proficiency in Python or Go (Golang), with a focus on building production-quality services. Experience working with More ❯

premise Kubernetes clusters Implement and maintain ML Ops pipelines using Kubeflow and similar tools (e.g., MLflow) Develop scripts and tooling in Python; manage Linux system configurations Leverage AWS infrastructure (Cognito, S3, EC2, Lambda, etc.) Integrate ML toolkits (e.g., PyTorch, Lightning) into ML Ops workflows Design and deploy robust ML Ops solutions across various technologies Contribute to the technical strategy … Experience: Solid experience managing on-premise Kubernetes clusters Strong knowledge of Kubeflow or similar ML Ops platforms Proficiency in Python programming, Linux systems, and scripting Experience with AWS services (Cognito, S3, EC2, Lambda, etc.) Familiarity with ML frameworks such as PyTorch or Lightning, and understanding their role in ML Ops pipelines Ability to design and implement comprehensive ML Ops More ❯

premise Kubernetes clusters Implement and maintain ML Ops pipelines using Kubeflow and similar tools (e.g., MLflow) Develop scripts and tooling in Python; manage Linux system configurations Leverage AWS infrastructure (Cognito, S3, EC2, Lambda, etc.) Integrate ML toolkits (e.g., PyTorch, Lightning) into ML Ops workflows Design and deploy robust ML Ops solutions across various technologies Contribute to the technical strategy … Experience: Solid experience managing on-premise Kubernetes clusters Strong knowledge of Kubeflow or similar ML Ops platforms Proficiency in Python programming, Linux systems, and scripting Experience with AWS services (Cognito, S3, EC2, Lambda, etc.) Familiarity with ML frameworks such as PyTorch or Lightning, and understanding their role in ML Ops pipelines Ability to design and implement comprehensive ML Ops More ❯