Devops Engineer Machine Learning
Resume:
RA
REDDY ABHILASH
DevOps Engineer
+1-940-***-**** ***************@*****.*** linkedin.com/abhilash Dallas EXPERIENCE
DevOps Engineer
One data software solutions
Architected and deployed 3 serverless applications using AWS Lambda and API Gateway, handling 500+ concurrent users while maintaining response times under 100ms
Engineered 2 data pipelines using AWS Glue and Redshift, processing 50GB daily data loads while ensuring data accuracy and completeness Implemented and optimized 4 machine learning models using AWS Sage Maker, reducing model training time by 40% while maintaining 90% prediction accuracy
Built and managed CI/CD pipelines using AWS Code Pipeline, reducing deployment time for cloud applications
Designed and implemented 6 monitoring dashboards using CloudWatch, providing real-time visibility into 25+ system metrics Created Infrastructure as Code templates using AWS CloudFormation, enabling rapid environment provisioning while maintaining consistency DevOps Engineer
ULE Systems
08/2023 - 08/2024 Dallas, TX
Engineered and maintained CI/CD pipelines using Jenkins, reducing deployment time while improving success rate
Implemented Infrastructure as Code using Terraform to automate 20+ AWS resource provisioning across 3 environments
Developed monitoring solutions using Nagios and CloudWatch, reducing system downtime by 60% through 15+ proactive alert configurations Streamlined container orchestration with Kubernetes, managing 3 clusters with 30+ microservices while ensuring 99.9% availability Automated security patch management across 50+ servers, maintaining compliance standards while reducing patching time by 70% Created disaster recovery procedures and backup strategies, achieving recovery objectives while ensuring data integrity
Junior DevOps Engineer
TATA Consultancy Services
12/2020 - 07/2022 Location
Collaborated with 4 development teams to maintain Jenkins pipelines, supporting continuous integration for 8 project teams Automated server configuration using Ansible playbooks, reducing setup time from 4 hours to 45 minutes per environment
Created and maintained 20+ Docker containers, managing image repositories while reducing resource utilization by 40% Implemented AWS cloud infrastructure including 15 EC2 instances and 3 VPC configurations across 2 regions
Developed 30+ shell scripts for routine maintenance tasks, reducing manual effort by 6 hours per week
Assisted in monitoring system metrics using Nagios, achieving 15-minute average response time for critical alerts
SUMMARY
Results-focused DevOps Engineer with 3.4 years
of hands-on experience in cloud infrastructure
automation and CI/CD implementation,
complemented by a master's in information
systems and technology. Strong foundation in AWS
cloud services, container orchestration, and
Infrastructure as Code practices. Demonstrated
success in optimizing deployment workflows and
collaborating with development teams to deliver
resilient infrastructure solutions.
LANGUAGES
English
Advanced
SKILLS
Ansible Apache API
API Gateway Automated Testing
AWS AWS Cloud AWS Glue
AWS Lambda CI/CD
Cloud Infrastructure Cloud Services
Cloudformation Cloudwatch
Configuration Containers
Data Integrity Devops
Disaster Recovery Docker EC2
ELB ELK ELK Stack Git
Github HIPAA IAM Jenkins
Junit Kubernetes Lambda Linux
Machine Learning Maven
Microservices
Microservices Architecture Nagios
Python Redshift
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E q
EXPERIENCE
Healthcare Analytics Platform - Containerized
Microservices Architecture
Unspecified
Date period Unspecified
Engineered end-to-end CI/CD pipeline using Jenkins and Git for a customer-facing portal handling 10,000+ daily transactions Implemented automated testing frameworks including SonarQube and JUnit, achieving 85% code coverage
Created Jenkins jobs for build, test, and deployment stages, enabling seamless integration with AWS services
Developed custom scripts for database migration and backup, ensuring zero data loss during deployments
Orchestrated deployment of microservices using Kubernetes and Helm charts for a HIPAA-compliant healthcare analytics platform Improved application scalability through container orchestration, handling 3x increase in user load
Implemented centralized logging using ELK stack, aggregating logs from 20+ service endpoints
Designed high-availability architecture using AWS EKS, maintaining 99.9% uptime
Created automated scaling policies based on CPU and memory metrics, optimizing resource utilization
EDUCATION
Master of Science in Information Systems and
Technology
University of North Texas
08/2022 - 05/2024 Denton
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