Job Description :
Project Location: Los Angeles, CA
Duration: 12-18 Months Start Date: Immediate Pay-rate: Market
Position Summary: We are looking for AWS Cloud DevOps Engineer to build our cloud based machine learning applications. Looking for a senior resource with proven hands on experience in managing an enterprise Machine learning platform on AWS Cloud.
Overall 6+ years of experience with minimum at least 2 years on the below skillset/ experience
Strong experience in setting up the enterprise infrastructure on Amazon Web Services (AWS) like EC2 instance, ELB, EBS, S3 Bucket, Security Groups, Auto scaling, AMI, RDS, IAM Cloud formation, Active directory Connector, Workspaces, Cloud Front & VPC services using Terraform, PowerShell Scripts, and JSON scripts.
Good understanding on DevOps tools such as GIT, SVN, ANT, Maven, Chef, Puppet, Ansible, Vagrant, Virtual Box, Jenkins, and Docker.
Configuration and maintenance of all networks, firewall, storage, load balancers, operating systems and software in AWS EC2.
Use Amazon IAM tool and create groups & permissions for users to work collaboratively.
Managing Custom AMI''s, Creating AMI snapshots and modified AMI permissions. – This is a MUST
Troubleshooting AWS Auto scaling and EC2 instances related issues.
Configure AWS Elastic Load balancer with backend applications.
Configure ELB or ALB with EC2 Auto scaling groups and Installation of EC2 instances for production, Testing and Development environment.
Experienced in Configured AWS Identity and Access Management (IAM) Groups and Users for improved login authentication.
Build S3 buckets and manage policies for S3 buckets & use S3 bucket and glacier for storage and backup on AWS.
Create templates (Stacks) in Cloud Formation to Ship all the logs (VPC-flow-logs, EC2, RDS, Cloud trail, cloud watch) and point to one S3 bucket.
Create Amazon Virtual Private Cloud to create public-facing subnet for web servers with internet gateway, and backend databases & application servers in a private-facing subnet.
Experience with Atlassian tools like Bamboo & Jira.
Create customized AMIs based on already existing AWS EC2 instances by using create image functionality, to be used for Disaster recovery
Create AWS Launch configurations based on customized AMI and use this launch configuration to configure auto scaling groups and Implement AWS solutions using EC2, S3, RDS, DynamoDb, Route53, EBS, Elastic Load Balancer.
Experience with Datadog monitoring
Gitlab integration and interaction.
             

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