Senior DevOps Engineer Multi-Cloud & MLOps Expert

Vijaya Manideep Annamaneni

****************@*****.*** 901-***-**** USA LinkedIn

Summary

DevOps Engineer with 5+ years of experience in multi-cloud platforms (AWS, Azure, GCP), containerization, CI/CD, GitOps, and DevSecOps. Skilled in designing scalable cloud infrastructures, automating deployments, and implementing security and compliance best practices. Expert in MLOps, observability, and scripting for enterprise settings, driving efficiency, reliability, and operational excellence across cloud-native applications and services. Technical Skills

• Cloud Platforms & Services (Multi-Cloud): AWS (EKS, Lambda, CloudTrail, S3, RDS, DynamoDB, Glue, EventBridge, SageMaker, Cost Explorer, GuardDuty, CodePipeline, CodeBuild), Azure (AKS, Azure SQL, Blob Storage, Azure ML, ARM Templates, Bicep, Azure Security Center, Defender for Cloud, Azure Functions), Google Cloud Platform (GCP)

• IaC & Configuration Management: Terraform, AWS CloudFormation, ARM Templates, Bicep, Ansible, Chef, Puppet, Policy as Code (HashiCorp Sentinel, OPA), Terraform Modules, Infrastructure Validation (Pester, Inspec, Checkov, Terratest)

• Containerization & Orchestration: Docker, Kubernetes (EKS, AKS), Helm, Istio (service mesh), Flux/CD, ArgoCD, Kubeflow

• CI/CD & GitOps: Jenkins, GitLab CI, Azure DevOps, AWS CodePipeline, AWS CodeBuild, GitHub Actions, CircleCI, Bitbucket Pipelines, Travis CI, Bamboo, ArgoCD, Flux, Tekton, Spinnaker, Harness, GitOps workflows, Blue-Green and Canary Deployments

• Security & DevSecOps: OWASP ZAP, SonarQube, Snyk, Trivy, Aqua Security, HashiCorp Vault, Azure Security Center, Defender for Cloud, Security Automation, Shift-Left Security, DevSecOps, Compliance (PCI DSS, SOX, HIPAA, GDPR, SOC 2), IAM Best Practices, Zero Trust

• Observability, Monitoring & Logging: Prometheus, Grafana, ELK Stack (Elasticsearch, Logstash, Kibana)

• MLOps & AI Integration: AWS SageMaker, Azure ML, MLflow, Kubeflow, Kafka, AI-driven Automation, Model Versioning & Validation, AIOps

• Scripting & Automation: Python, Bash, PowerShell, C

• Version Control & Collaboration: Git (GitHub, GitLab), GitOps workflows, Confluence, Notion, Azure Wiki Professional Experience

DevOps Engineer, Discover Financial Services 07/2024 – Present Remote, USA

• Engineered an AI-driven financial analytics platform to deliver personalized financial insights, real-time fraud detection, and predictive transaction monitoring using AWS EKS, SageMaker, and Kafka. Partnered with product, data, and architecture teams to define cloud architecture, scalability targets, and compliance standards.

• Developed automated CI/CD pipelines with GitHub Actions, ArgoCD, Terraform, and AWS CodePipeline, integrating ML model validation and Bash scripting for build orchestration. Optimized Java and Python services, increasing deployment efficiency and reducing rollback incidents.

• Designed containerized infrastructure using Docker, Kubernetes, and Helm with GitOps workflows for AI microservices. Achieved 99.995% uptime and reduced infrastructure costs by 30% through efficient cluster autoscaling and environment optimization.

• Built MLOps pipelines integrating Kubeflow, MLflow, and SageMaker for AI model training, retraining, version control, and CI/CD for fraud detection and credit risk prediction. Increased deployment rate by 70% and enhanced model accuracy monitoring with Prometheus.

• Implemented observability and security automation using OpenTelemetry, Datadog, Grafana, and HashiCorp Vault, establishing continuous policy enforcement and automated secrets rotation workflows. Improved system reliability by 55% and achieved SOC 2 and PCI DSS compliance readiness.

• Collaborated with SRE, security, QA, and documentation teams to create standardized IaC blueprints, runbooks, and operational playbooks using Confluence and Notion. Introduced chaos testing, A/B validation, and incident retrospectives to enhance system resilience by 40%. DevOps Engineer, eBay 05/2023 – 07/2024 Remote, USA

• Designed and deployed scalable CI/CD pipelines using GitHub Actions, Jenkins, and ArgoCD, enabling automated deployment of microservices and AI-powered recommendation systems, reducing release times by 40% while maintaining high reliability and observability.

• Implemented containerized infrastructure with Kubernetes, Docker, and Helm, integrating GitOps workflows for real-time auto-scaling AI services. Optimized resource utilization, achieving 99.99% uptime and reducing cloud costs by 25% across multiple e-commerce platforms.

• Built MLOps pipelines for AI-driven product recommendations and fraud detection, leveraging Kubeflow, MLflow, and AWS SageMaker. Enhanced model versioning, monitoring, and retraining processes, boosting deployment frequency and predictive accuracy by 60%. DevOps Engineer, HCL Technologies Limited 01/2019 – 06/2021 Tamil Nadu, India

• Designed and applied Azure cloud infrastructure for enterprise digital transformation initiatives using Terraform, Bicep, and ARM templates, automating provisioning workflows, enforcing governance policies, and improving setup delivery efficiency by 50% across production workloads.

• Developed CI/CD pipelines for application modernization programs using Azure DevOps, GitHub Actions, Docker, Helm, and Argo CD, enhancing deployment reliability by 95%, accelerating release velocity by 50%, and minimizing rollbacks for microservices-based applications.

• Strengthened cloud security and compliance using Azure Defender, Snyk, Trivy, and HashiCorp Vault, increasing vulnerability remediation efficiency by 70%, reducing misconfigurations by 80%, and enhancing governance across regulated enterprise environments.

• Automated machine learning workflows for enterprise analytics platforms using Azure ML, MLflow, and Kubeflow, streamlining model training, validation, and deployment, improving anomaly detection accuracy by 30%, and reducing incident response times by 35%.

• Integrated observability and monitoring using Prometheus, Grafana, Loki, and OpenTelemetry, defining SLIs and SLOs, enabling automated alerting, reducing mean time to recovery (MTTR) by 60%, and increasing proactive incident detection by 55%.

• Implemented policy-driven compliance automation using Terratest, Checkov, InSpec, and OPA, improving policy coverage by 100%, minimizing configuration drift by 75%, and standardizing Terraform modules across multiple environments to ensure operational reliability.

• Developed infrastructure automation scripts using Bash, Python, and policy-driven pipelines, reducing manual governance efforts by 68%, improving configuration consistency by 80%, and ensuring continuous compliance across enterprise cloud deployments. Education

Master’s Degree in Computer Science 07/2021 – 07/2023 Wichita State University, Wichita, KS, USA

Bachelor’s Degree in Computer Science and Engineering 07/2015 – 07/2019 Sathyabama Institute of Science and Technology, Chennai, India

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