Cloud Ops Lead

Role : Cloud Ops Lead

Location : Onsite New York

Primary Skills : AWS Cloud Solutions and Operations, Architecting and Automation of Cloud Infrastructure, AI / ML Integration

Secondary Skills : Good experience in automation scripts such as PowerShell, AWS CLI, Python, JSON, and familiarity with AI / ML frameworks and tools.

Responsibilities :

Architect, design, and implement scalable, secure, and cost-optimized cloud solutions leveraging the latest AWS offerings, including generative AI services (e.g., Amazon Bedrock, SageMaker, Amazon Q, CodeWhisperer).

Deep, hands-on technical expertise in AWS, including new services such as Lambda SnapStart, Graviton-based compute, and advanced analytics (e.g., Amazon QuickSight, Redshift Serverless).

Support and administration of AWS IaaS and PaaS, including RDS, Athena, DynamoDB, EFS, ElastiCache, Kinesis Firehose, S3, Route53, SNS, Lambda, Data Pipeline, and new AI / ML services.

Implement and manage monitoring, analytics, and optimization tools (AWS CloudWatch, AWS CloudTrail, AWS Cost Explorer, and AI-driven observability tools).

Operational understanding of securing cloud instances, including AI-powered security tools (e.g., Amazon GuardDuty, Macie, Inspector).

Expertise in Linux administration, AWS VPC, subnet management, and troubleshooting.

Develop and maintain cloud automation scripts / code (Perl, JSON, PowerShell, Terraform, AWS CloudFormation, CDK), including integration with AI / ML pipelines.

Identify and resolve cloud performance bottlenecks using architectural and AI-driven performance analytics.

Analyze AWS CloudTrail logs and aggregated log files for advanced troubleshooting, leveraging AI-based log analysis where appropriate.

Identify and implement cost-saving strategies using AWS's latest cost management and AI-powered optimization tools.

Understanding of Cloud Platform Engineering, SRE, and AI / ML Ops best practices.

Good knowledge of application build / release processes, CI / CD pipelines (Jenkins, Chef / Puppet, AWS CodePipeline, CodeBuild, and integration with AI-powered DevOps tools).

Familiarity with Agile processes and ability to collaborate with cross-functional teams (Development, Infrastructure, Security, Testing, QA, and Data Science / AI teams).

Analyze customer business and technical requirements, assess environments for cloud and AI enablement, and advise on cloud and AI / ML solutions and risk management.

Participate in customer cloud and AI / ML pre-sales responses and projects.

Strong passion for technology exploration, AI / ML development, and continuous learning.

Excellent written and verbal communication, presentation, and collaboration skills.

Team leadership skills.

NICE TO HAVE

Assist with backups and recovery, including AI-driven backup optimization.

Deploy applications, performance tuning, troubleshooting, maintain security, and automate routine procedures through scripting and AI-based automation.

Integrate 3rd party tools, APIs, and AI / ML services in AWS environments.

Knowledge of ServiceNow and its integration with AWS and AI / ML workflows is recommended"