DevOps Engineer: Cloud Automation & GitOps Specialist

Athish Venkatachalam

Fremont, CA +1-864-***-**** ******************@*****.*** LinkedIn

SUMMARY

DevOps Engineer with 3+ years of experience automating CI/CD pipelines, provisioning scalable cloud infrastructure, and building secure, observable deployment ecosystems. Proficient in AWS, Azure, Terraform, Ansible, Helm, and Argo CD, with strong expertise in container orchestration, GitOps practices, and production-grade monitoring. Knowledgeable at integrating DevSecOps controls, optimizing performance, and reducing operational overhead through automation. Proficient in managing multi-environment workloads, improving deployment reliability, and enabling seamless collaboration between development and operations teams. Committed to delivering high-availability systems, cost- efficient cloud architectures, and continuous improvement across the software delivery lifecycle. TECHNICAL SKILLS

Programming & Scripting: Python, Go, Bash/Shell, TypeScript, JavaScript, SQL Cloud Platforms: AWS (EKS, ECS, Lambda, API Gateway, DynamoDB, Route53, CDK, CloudFormation, SQS/SNS), Azure (AKS, Bicep, DevOps Pipelines)

IaC & Automation: Terraform, Ansible, Pulumi, CDK, Azure Bicep, Crossplane, Serverless Framework Containers & Orchestration: Docker, Kubernetes (EKS/AKS), Helm, Argo CD, Argo Rollouts, Ingress Controllers (NGINX/Traefik), External-DNS CI/CD & DevOps: GitHub Actions, Jenkins, GitLab CI/CD, Azure DevOps, Nexus, SonarQube, GitOps workflows, build-test-deploy pipelines Monitoring & Observability: Prometheus, Grafana, Loki, ELK Stack, OpenTelemetry, AWS CloudWatch, Azure Monitor Security & Compliance: HashiCorp Vault, Trivy, Checkov, OPA/Kyverno, IAM, RBAC, OAuth2, Secrets Management Databases: MySQL, PostgreSQL, MongoDB, Redis, Amazon RDS/Aurora, DynamoDB Streams MLOps & Automation: Kubeflow, MLflow, KServe, Airflow, vLLM (familiar), Workflow Automation, Serverless Cron Jobs Networking: Ingress, External-DNS, NSGs, Load Balancing, Auto Scaling Tools & Methods: Agile/Scrum, Jira, Git, Microservices, API Testing (Postman, Selenium), Performance Testing, FinOps (Kubecost) PROFESSIONAL EXPERIENCE

SentiLink, USA

Associate DevOps Engineer – I Jan 2025 – Current

• Architected CI/CD pipelines with GitHub Actions, Jenkins, and Argo CD to accelerate secure production delivery for fraud-detection services, cutting deployment time by 18 minutes and enabling daily releases.

• Engineered AWS EKS orchestration with Helm and Argo Rollouts, supporting 120+ progressive deployments while keeping total downtime under 9 hours for identity-verification workloads.

• Automated infrastructure provisioning using Terraform and Ansible, standardizing environments and reducing effort by 6+ hours per.

• Built an observability stack with Prometheus, Grafana, Loki, and OpenTelemetry, improving visibility and lowering MTTR by 25 minutes.

• Integrated Vault, Trivy, and Checkov into CI/CD pipelines to eliminate hard-coded secrets and maintain zero audit violations.

• Enhanced networking with External-DNS and NGINX Ingress, reducing manual DNS maintenance by 10+ hours and improving routing. Infosys, Chennai, India

Jr. DevOps Engineer Aug 2021 – Jul 2023

• Developed reusable Terraform modules and CloudFormation stacks for EKS, RDS, and IAM resources, reducing provisioning effort by nearly hours per environment across multiple high-scale client deployments.

• Migrated legacy CI/CD pipelines from Jenkins to GitOps workflows using Argo CD and Helm, enabling fully declarative deployments and significantly minimizing configuration drift across distributed services.

• Containerized 20+ microservices using Docker and Kubernetes, introducing streamlined health checks and AWS CloudWatch monitoring to greatly improve deployment stability and operational visibility.

• Deployed and maintained Nexus and SonarQube for artifact management and code quality checks, improving pipeline reliability and strengthening overall DevSecOps compliance standards.

• Partnered with teams to implement IAM, RBAC, and OAuth2, reducing access incidents by 30 tickets each quarter through enforcement.

• Supported knowledge-sharing on Terraform best practices and CI/CD automation, standardizing workflows and improving team alignment. DevOps Intern Feb 2021 – Jul 2021

• Assisted in containerizing Node.js/Java apps and authored Terraform modules for VPC, subnets, and NAT to improve deployment consistency across environments.

• Streamlined operations tasks—backups, AMI snapshots, log rotation—using Bash and Ansible, saving 15 engineer-hours weekly.

• Contributed to Jenkins pipelines by adding linting, testing, and Trivy scans, improving checks and preventing 35–40 failures per quarter.

• Participated in Agile sprints and release planning, supporting 20+ production workloads and enabling 8–10 deployments each cycle. PROJECTS

CloudOps360 — Self-Healing GitOps Platform (AWS + Azure) Terraform, Argo CD, Helm, EKS/AKS, Ansible, Prometheus, Grafana, Loki, Vault, External-DNS

• Built a self-healing GitOps platform across AWS and Azure by integrating Terraform modules, Argo CD, Helm, Vault, and Ansible, delivering one-click environment provisioning, eliminating configuration drift, and blocking 40–50 insecure changes per release through security scans.

• Implemented unified observability and networking with Prometheus, Grafana, Loki, External-DNS, and NGINX Ingress, improving SLO/SLI visibility across 6+ clusters, reducing alert diagnosis time by 15–20 minutes, and cutting manual work by 12 engineer-hours monthly. SmartScaleAI — Predictive Scaling & Cost Optimization (AWS) Python, AWS Lambda, Step Functions, CloudWatch, EKS Autoscaling, Kubecost, MLflow

• Constructed a predictive autoscaling system using MLflow models, CloudWatch signals, Lambda, and Step Functions to forecast EKS demand, improving scaling responsiveness and reducing compute usage by 120–180 hours monthly while maintaining SLA-level performance.

• Implemented Kubecost cost-visibility dashboards and automated model-retraining via GitHub Actions, enabling daily spend tracking across 15+ services, detecting 5–7 anomalies monthly, and supporting 30+ retraining cycles to keep models accurate under 2–3 workload spikes. EDUCATION

Master of Science in Computer Science May 2025

Clemson University, Clemson, SC

Bachelor of Technology in Computer Science and Business Systems May 2023 SRM Institute of Science and Technology, India

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