Job
Description
We are looking for a highly skilled and experienced AWS Cloud Native AI Engineer with 5 to 10 years of experience. The ideal candidate will have expertise in Python, GenAI, and AWS cloud services. ### Roles and Responsibility Design and develop cloud-native applications and services using AWS services such as Lambda, API Gateway, ECS, EKS, DynamoDB, Glue, Redshift, EMR. Implement CI/CD pipelines using AWS CodePipeline, CodeBuild, and CodeDeploy to automate application deployment and updates. Collaborate with architects and other engineers to design scalable and secure application architectures on AWS. Monitor application performance and implement optimizations to enhance reliability, scalability, and efficiency. Implement security best practices for AWS applications, including identity and access management (IAM), encryption, and secure coding practices. Design and deploy containerized applications using AWS services such as Amazon ECS (Elastic Container Service), Amazon EKS (Elastic Kubernetes Service), and AWS Fargate. Optimize container performance and resource utilization by tuning settings and configurations. Implement and manage application observability tools such as AWS CloudWatch, AWS X-Ray, Prometheus, Grafana, and ELK Stack (Elasticsearch, Logstash, Kibana). Develop and configure monitoring, logging, and alerting systems to provide insights into application performance and health. Create dashboards and reports to visualize application metrics and logs for proactive monitoring and troubleshooting. Integrate AWS services with application components and external systems, ensuring smooth and efficient data flow. Diagnose and resolve issues related to application performance, availability, and reliability. Create and maintain comprehensive documentation for application design, deployment processes, and configuration. ### Job Requirements Proficiency in AWS services such as Lambda, API Gateway, ECS, EKS, DynamoDB, S3, and RDS, Glue, Redshift, EMR. Experience in developing and deploying AI solutions with Python and JavaScript. Strong background in machine learning, deep learning, and data modeling. Good understanding of backend development using NodeJS, ExpressJS, Python Flask/FastAPI, and RESTful API design. Proficiency in frontend development using Angular, ReactJS, TypeScript. Experience with cloud engineering technologies like Docker, Git, and CI/CD pipelines. Understanding of AWS security best practices, including IAM, KMS, and encryption. Familiarity with observability tools like AWS CloudWatch, AWS X-Ray, Prometheus, Grafana, and ELK Stack. Knowledge of container orchestration concepts and tools, including Kubernetes and Docker Swarm. Monitoring and logging tools such as AWS CloudWatch, CloudTrail, or ELK Stack. Strong teamwork and communication skills with the ability to work effectively with cross-functional teams.
