Senior DevOps Engineer

– Orchestrated and managed enterprise-level applications across 300+ AWS accounts, utilizing S3, CloudFront, ECS (EC2 & Fargate), ECR, EKS, RDS, API Gateway, Lambda, ALB/NLB, SNS, SQS, Step Functions, and Route 53. – Established comprehensive Infrastructure as Code (IaC) using Terraform and CloudFormation with modular design patterns, remote state management (S3 + DynamoDB locking), and reusable modules — enabling rapid environment provisioning across multi-account setups. – Designed and implemented fully automated CI/CD pipelines using Jenkins, GitHub Actions, and AWS CodeDeploy, reducing deployment lead time by 60% and enabling continuous delivery across multiple environments. – Designed self-healing Kubernetes clusters on EKS with automated rollouts, rollbacks, horizontal pod autoscaling (HPA), and cluster autoscaler to handle fluctuating enterprise traffic with zero manual intervention. – Operationalized AWS security services (SecurityHub, Config, GuardDuty) using AWS Organizations, configured custom suppression rules, and built proactive alerting workflows with Lambda, SQS, and Step Functions. – Led cloud cost optimization across 300+ AWS accounts — implemented right-sizing, Reserved Instance planning, S3 lifecycle policies, and unused resource cleanup, achieving a 30% reduction in monthly cloud spend. – Built a multi-agent AI platform using Google ADK with an agentic approach — integrating security and operational tools (Jira, Splunk, CrowdStrike, Hunters SIEM) via REST APIs to autonomously correlate findings, generate real-time vulnerability reports, and trigger remediation workflows, reducing detection-to-report time by 70%. – Integrated security into CI/CD pipelines (DevSecOps) including SAST, DAST, container image scanning, and IaC validation using Checkov — shifting security left and cutting manual review time by 40%. – Defined and enforced security and license policies for the engineering department, including RBAC, secrets management (AWS Secrets Manager, KMS), and SSO/SAML integrations. – Deployed and managed AI/ML model serving infrastructure on AWS — provisioned SageMaker endpoints, containerized inference services on ECS/EKS, and built CI/CD pipelines for model versioning, A/B testing, and automated rollback of ML models in production. – Set up end-to-end MLOps workflows including model artifact storage (S3), container image builds for inference (ECR), API Gateway integration for model endpoints, and CloudWatch-based monitoring for model drift and latency tracking. – Automated AI application deployments using Terraform and Lambda — provisioning Bedrock foundation model access, SageMaker notebook environments, and supporting data engineering pipelines for training data preparation across S3 and Glue. – Implemented automated Access Key lifecycle management across 250+ accounts

– Evaluated and integrated security tools into CI/CD pipelines, automating vulnerability scanning and compliance checks as part of the build process. - Configured SecurityHub, AWS Config, AWS GuardDuty, and CloudWatch alerts using IaC (Terraform/CloudFormation) to maintain continuous compliance posture. - Designed production architecture with zero downtime using Blue/Green deployment strategies on ECS and EKS. – Managed and mentored a team of three across DevOps and Infrastructure, driving adoption of automation-first practices. – Configured auto-scaling groups for EC2 nodes and Kubernetes pod autoscaling (HPA/VPA) to handle dynamic workloads cost-effectively. – Set up Kubernetes dashboards and integrated APM monitoring for EKS cluster metrics, enabling proactive performance management. – Configured infrastructure and APM monitoring across all production services with customized threshold profiles for trouble and critical alerts. – Audited security vulnerabilities across cloud infrastructure and orchestrated patching workflows for servers and container images.

- Designed and managed end-to-end deployment pipelines using Jenkins and Bitbucket Pipelines with Groovy and YAML, supporting multi-environment delivery workflows. - Containerized standalone applications using Docker and deployed across multiple environments, establishing standardized build and runtime practices. - Configured multistage build pipelines with SAST integration and quality gate checks, enforcing code quality and security standards before production deployments. - Set up ELK stack for centralized logging and monitoring, enabling unified observability and faster incident response. - Worked with the infra-clean-task-force to optimize cloud inventory, identify underutilized resources, and reduce overall cloud costs. - Set up CI/CD pipelines for mobile applications with automated internal distribution via Microsoft App - Center and production releases to App Store and Play Store. - Implemented Jenkins declarative pipelines with Groovy scripting for one-click deployments, reducing deployment complexity and human error.

- Planned, scheduled, and controlled installation and deployment processes from scratch, ensuring all project requirements were delivered on time. - Set up CI/CD pipelines for C# ASP.NET applications deployed on Windows Server IIS 10 through Jenkins. - Built and maintained deployment automation using Jenkins declarative pipelines with Groovy scripting. - Assembled technical documentation and prepared presentations for development teams to standardize the deployment process.