1,026 to 1,050 of 9,144 AWS Jobs

JavaScript, C#, or similar). Bring solid DevOps and infrastructure engineering skills. Have hands-on experience with Kubernetes, Terraform, and CI/CD pipelines. Understand cloud environments (Azure preferred, AWS/GCP also great). Care deeply about building reliable systems that make a real-world impact. 💡 Bonus Points For Experience working in AI, Biotech, or other data-intensive domains. More ❯

Data Engineer: Design, build, and maintain scalable data pipelines and architectures, ensuring reliability, performance, and best-in-class engineering standards Leverage Databricks, Spark, and modern cloud platforms (Azure/AWS) to deliver clean, high-quality data for analytics and operational insights Lead by example on engineering excellence, mentoring junior engineers and driving adoption of DevOps and CI/CD best More ❯

Redis, Oracle Messaging & Streaming: Apache Kafka DevOps & CI/CD: GitLab CI/CD, Jenkins, Docker, Kubernetes Cloud & Storage: IBM Cloud, Cloud Object Storage Infrastructure as Code (IaC): Terraform, AWS CloudFormation Version Control: Git About Capgemini: Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world while creating More ❯

Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate More ❯

Redis, Oracle Messaging & Streaming: Apache Kafka DevOps & CI/CD: GitLab CI/CD, Jenkins, Docker, Kubernetes Cloud & Storage: IBM Cloud, Cloud Object Storage Infrastructure as Code (IaC): Terraform, AWS CloudFormation Version Control: Git About Capgemini: Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world while creating More ❯

Knowledge of Custom Application Development within ServiceNow Additional Certifications: ServiceNow Certified Application Developer (CAD) Certifications in ITSM, ITOM, HRSD, or IntegrationHub Integration Tools: Familiarity with IntegrationHub Spokes (e.g., Azure, AWS, Microsoft Teams) DevOps and CI/CD: Experience using Git, Jenkins, or ServiceNow App Repo for version control and deployment Agile/Scrum Methodology: Experience working in Agile environments with More ❯

Redis, Oracle Messaging & Streaming: Apache Kafka DevOps & CI/CD: GitLab CI/CD, Jenkins, Docker, Kubernetes Cloud & Storage: IBM Cloud, Cloud Object Storage Infrastructure as Code (IaC): Terraform, AWS CloudFormation Version Control: Git About Capgemini: Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world while creating More ❯

with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem More ❯

with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem More ❯

Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate More ❯

Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate More ❯

with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem More ❯

Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate More ❯

Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate More ❯

with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem More ❯

with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). Experience with data engineering concepts — ETL pipelines, data lakes, and cloud data platforms. Proficiency with cloud services (AWS, Azure, or GCP) for model deployment and orchestration. Knowledge of containerization and orchestration tools (Docker, Kubernetes). Experience integrating ML models into production environments via APIs or microservices. Excellent problem More ❯

Neo4j or Amazon Neptune. Strong understanding of distributed systems, API design, and modern deployment practices using Docker, Kubernetes, and CI/CD pipelines. Comfort working in cloud-based environments (AWS preferred), including data connectivity and infrastructure-as-code principles. Experience integrating LLMs, RAG pipelines, or vector databases into production workflows is a major plus. A strong communicator who can translate More ❯

additional tools such as Python, R, IBM Watson, and Power BI. Understanding of DevOps tools (Git, Azure DevOps, Jenkins, Docker, Kubernetes). Experience working with Cloud Service Providers (Azure, AWS, GCP). More ❯

Redis, Oracle Messaging & Streaming: Apache Kafka DevOps & CI/CD: GitLab CI/CD, Jenkins, Docker, Kubernetes Cloud & Storage: IBM Cloud, Cloud Object Storage Infrastructure as Code (IaC): Terraform, AWS CloudFormation Version Control: Git About Capgemini: Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world while creating More ❯

Agile/SCRUM environment. * Familiarity with CCSDS standards or ECSS data communications protocols. * Schema database formats (SCOS2000/XTCE, etc) * Working in Ground Segment systems. * Cloud platforms such as AWS or Azure. * Knowledge of security best practices in software development. What you'll get in return * Competitive salary and benefits package. * Flexible and hybrid working options, including every other Friday More ❯

Agile/SCRUM environment.* Familiarity with CCSDS standards or ECSS data communications protocols.* Schema database formats (SCOS2000/XTCE, etc)?* Working in Ground Segment systems.* Cloud platforms such as AWS or Azure.??* Knowledge of security best practices in software development. What you'll get in return * Competitive salary and benefits package.* Flexible and hybrid working options, including every other Friday More ❯

Agile/SCRUM environment. * Familiarity with CCSDS standards or ECSS data communications protocols. * Schema database formats (SCOS2000/XTCE, etc) * Working in Ground Segment systems. * Cloud platforms such as AWS or Azure. * Knowledge of security best practices in software development. What you'll get in return * Competitive salary and benefits package. * Flexible and hybrid working options, including every other Friday More ❯

Agile/SCRUM environment. * Familiarity with CCSDS standards or ECSS data communications protocols. * Schema database formats (SCOS2000/XTCE, etc) * Working in Ground Segment systems. * Cloud platforms such as AWS or Azure. * Knowledge of security best practices in software development. What you'll get in return * Competitive salary and benefits package. * Flexible and hybrid working options, including every other Friday More ❯

products Proficiency in Python and JavaScript/TypeScript (Node.js) Strong understanding of backend architectures, REST/GraphQL APIs, and data modelling Experience with containerisation (Docker) and cloud platforms ( GCP , AWS , or similar) Familiarity with LLM or AI APIs Exposure to agentic frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.) Practical experience with databases (SQL/NoSQL) Strong foundation in software design principles More ❯

products Proficiency in Python and JavaScript/TypeScript (Node.js) Strong understanding of backend architectures, REST/GraphQL APIs, and data modelling Experience with containerisation (Docker) and cloud platforms ( GCP , AWS , or similar) Familiarity with LLM or AI APIs Exposure to agentic frameworks (LangChain, LlamaIndex, Semantic Kernel, etc.) Practical experience with databases (SQL/NoSQL) Strong foundation in software design principles More ❯