Key Responsibilities: AWS Infrastructure Management: Design, implement, and manage AWS cloud infrastructure. Optimize AWS resources to ensure cost-effective and scalable solutions. Monitor and maintain AWS services including EC2, S3, RDS, Lambda, and more. Deployment and Release Management: Develop and maintain automated deployment scripts. Ensure smooth and efficient deployment processes. Troubleshoot and resolve deployment issues in a timely manner. More ❯
best practices 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 More ❯
roadmap and practices About you Have 5+ years' experience as a DevOps engineer Have in-depth practical experience working on AWS (VPC networking and security, IAM, EC2, Postgres RDS, S3, EKS) experience running production-level services in Kubernetes and managing and maintaining the cluster Practical experience automating the management of infrastructure with Terraform Experience in the configuration and running More ❯
an agile software development environment. Experience of source control (e.g., git) and issue tracking (e.g., JIRA) tools. Experience of object orientated programming principles. Experience of AWS (e.g., Lambda, Cognito, S3, DynamoDB). Demonstrated ability to share knowledge, concepts, and ideas to a wide range of people. Excellent written and verbal communication with strong interpersonal skills. Experience in mentoring others. More ❯
additional technologies (listed below) is advantageous: Kotlin Cloud Technologies (Kubernetes, Open Shift) Messaging Technologies (Kafka, Solace, TIBCO) Database/Data Store/Data Query Technologies (SQL Server, Trino, Mongo, S3) Observability Technologies (OpenTelemetry, Elastic Stack/ELK, Grafana) This job description provides a high-level review of the types of work performed. Other job-related duties may be assigned More ❯
understanding of image processing workflows, deep learning pipelines, and model evaluation. Familiarity with MLflow for tracking experiments, managing model lifecycle, or deploying models. Experience with AWS services such as S3, EC2, SageMaker, Lambda, or similar tools for model deployment and data pipelines. What you'll be doing: Research and develop solutions to complex business problems, working with large, unstructured More ❯
