126 to 150 of 366 Remote/Hybrid DynamoDB Jobs

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

Rails codebase, even if it's not where you've spent the most time. Cloud Native: Deep AWS across Lambda, S3, SQS, Kinesis, EventBridge, DynamoDB, Aurora/RDS, Redshift, and IAM. ML in Production: You've kept models serving correctly over time - versioning, dependency drift, feature plumbing, explainability. ...

including serverless architecture (Lambda, API Gateway), container orchestration (EKS), messaging (SNS/SQS, RabbitMQ), and data services (RDS PostgreSQL, ElastiCache/Redis, DynamoDB). Manage and evolve CI/CD pipelines - automating build, test, and deployment processes using GitLab CI, Gradle, Terraform, and Serverless Framework to enable rapid, consistent … without compromising code quality or security standards. Extensive hands-on experience with AWS - specifically Lambda, API Gateway, CloudFront, S3, SNS, SQS, EKS, ElastiCache, and DynamoDB - and a track record of deploying and operating production workloads in cloud environments. Advanced proficiency with PostgreSQL and other data stores (Redis/Valkey ...

including serverless architecture (Lambda, API Gateway), container orchestration (EKS), messaging (SNS/SQS, RabbitMQ), and data services (RDS PostgreSQL, ElastiCache/Redis, DynamoDB). Manage and evolve CI/CD pipelines - automating build, test, and deployment processes using GitLab CI, Gradle, Terraform, and Serverless Framework to enable rapid, consistent … without compromising code quality or security standards. Extensive hands-on experience with AWS - specifically Lambda, API Gateway, CloudFront, S3, SNS, SQS, EKS, ElastiCache, and DynamoDB - and a track record of deploying and operating production workloads in cloud environments. Advanced proficiency with PostgreSQL and other data stores (Redis/Valkey ...

leading role in building complex software or computing infrastructure that has been successfully delivered to customers - Experience with AWS Services including EC2, Lambda, S3, DynamoDB, SQS - Experience in Kubernetes, Docker or containers ecosystem, or experience managing full application stacks from the OS up through custom applications and experience ...

product features across the stack: UI, APIs, and data model. Develop in TypeScript on Node and use Pulumi to deploy AWS tech like Lambda, DynamoDB and API Gateway in a way that’s reproducible, reviewable, and safe to change. Design event-driven solutions that scale to millions of requests ...

working on a variety of technical challenges. Technology Stack Node/TypeScript or Go for primary software development. AWS Serverless Ecosystem – Lambda, API Gateway, DynamoDB, S3. Amazon Connect Customer and the custom‐built front‐end portal. Jenkins for infrastructure as code and CI/CD pipeline management. Monitoring & Logging ...

Code: Terraform, Terragrunt, Crossplane Programming Languages: Python, JavaScript, TypeScript Frameworks: Django Rest Framework, container-based services, Serverless architectures Databases: MongoDB, Postgres, ElasticSearch, and DynamoDB DevOps & Monitoring Tools: CircleCI, GitHub Actions, Kubernetes, Celery, EventBridge, DataDog Why is Prolific a great place to work We've built a unique platform that ...

have experience of working on distributed systems You're familiar with other technology in the stack including: AWS, IaC using Terraform, Docker, PostgreSQL, DynamoDB, CI/CD, GitHub actions, Blacksmith runners You're collaborative and pragmatic with great communication skills, keen to input into technical discussion and decision making ...

Beneficial/Nice to have skills and experience: Experience of using cloud services such as AWS and distributed systems such as Kafka, Kubernetes, S3, DynamoDB, MongoDB or any other NoSQL database Experience of working in investment bank or financial services industry This job description provides a high-level review ...

highest level of proficiency developing applications using most of the following: Strong Golang knowledge and experience Knowledge of AWS products like Lambdas, DynamoDB, etc but also comfortable in Azure and Azure devops environments Containerisation and IaC approach (Terraform, SST are definitely a plus) A good understanding of development methodologies ...