Cloud & DevOps Engineer with AWS Expertise

HARSH MASANE

New York 607-***-**** *******@**********.*** Linkedin GitHub

EDUCATION

Binghamton University, State University of New York, School of Computing, Binghamton, NY, USA Master of Science, Computer Science Aug 2024 – May 2026 Coursework: System Programming, Cloud Computing, Database Systems and Management Dwarkadas Jivanlal Sanghvi College of Engineering, Mumbai, India Bachelor of Engineering, Electronics Engineering Aug 2019 – May 2022 TECHNICAL SKILLS

•Languages: Python, Shell/Bash, Groovy, YAML, SQL

•OS & Database: Ubuntu, Linux, Windows, MySQL, MongoDB

•Networking: TCP/IP, UDP, DNS, IPv4/6, Subnet, Load Balancer, Troubleshooting

•Cloud Platforms: AWS(EC2, Lambda, IAM, CloudWatch, EKS, S3, VPC, RDS), GCP & Azure fundamentals

•DevOps Tools: Jenkins, Github, Docker, Kubernetes, Ansible, Terraform

•Version Control: GitHub, Bitbucket, SVN

•Monitoring: Grafana, Prometheus

PROFESSIONAL EXPERIENCE

Cloud/Infrastructure Intern(Remote) : Interlinked : Berkeley, CA, USA July 2025 – Dec 2025

• Designed and maintained AWS-based distributed infrastructure supporting AI-driven applications used by public agencies.

• Collaborated with engineers across backend, infrastructure, and data teams to support scalable cloud services. Student Assistant, Innovation Lab : Binghamton University : Binghamton, NY, USA Sept 2024 - Present

• Assisting 50+ students and instructors to manage the innovation lab space with technology.

• Managing windows, apple operating systems and online conferencing software tools. DevOps Engineer : Edelweiss Global Markets : Mumbai, India Jun 2022 - Aug 2024

• Building and supporting 20+ projects by CI/CD workflows using Jenkins, Bash, Python, and Groovy to reduce manual errors by 80%.

• Containerized services with Docker and developed a Groovy-based Jenkins pipeline that automatically builds, tags, and deploys images across different environments which boosted developer team efficiency by 90%.

• Defined and enforced access control policies across Bitbucket, SVN, and Sonatype-Nexus repositories to ensure secure configuration management and establish operational best practices.

• Designed a high-availability MongoDB cluster using Ansible that ensured 95% uptime.

• Developed backup and restoration scripts with Jenkins empowered data reliability with 96% efficiency and minimizing downtime in case of data loss.

• Reduced storage usage on production server by 0.5TB via daily cleanup script, optimizing server performance and life. PROJECTS

DevOps Knowledge Assistant: Local RAG-based semantic search system using LangChain & Ollama: Engineered an AI-powered retrieval assistant enabling contextual search across DevOps documentation by implementing document ingestion, chunking, embedding, and vector indexing with ChromaDB. Leveraged Ollama-hosted models for offline inference and designed modular architecture for future FastAPI exposure, containerization, and Kubernetes deployment. Impact: Enabled offline semantic search capability for technical documentation with deployable AI-assisted DevOps tooling. AutoDeployment Pipeline: End-to-end CI/CD pipeline automation for 2-Tier Java application on Linux: Integrated Jenkins, SVN, Maven, and Nexus for artifact versioning. Developed Python hooks for automated JIRA tagging, approval and Shell scripts for environment promotion(Dev/QA/Prod). Impact: Reduced 6-step manual deployment to fully automated 2-minute process, eliminating human error and enabling 3x daily release frequency. Database Install Automation: Automated database provisioning using Ansible & Jenkins CI/CD: Engineered end-to-end automation framework for installing and configuring MongoDB databases across 10+ servers. Developed parameterized Ansible playbooks with role-based architecture for database installation, user management, replication setup, and performance tuning. Integrated with Jenkins pipeline for automated deployment Impact: Reduced database provisioning time from 4 hours to 12 minutes, eliminated 90% of manual configuration errors, and enabled self-service database deployment Self-Healing Backup Monitor: Automated validation & remediation for MongoDB backups using Kubernetes: Deployed kube-state-metrics on AWS to monitor CronJob success, configured PromQL alerts with Alertmanager email routing, and built Python webhook for automatic job re-execution on failure. Created Grafana dashboards for root cause analysis (CPU/RAM/disk) Impact: Reduced backup failures by 95% (weekly to <1/quarter) and cut recovery time by 98% (8 hrs to 10 min). CERTIFICATIONS

• DevOps Engineering on AWS with Jam – July, 2023

• AWS Cloud Practitioner (CLF-C02) – Pursuing

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