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Devops Engineer with 1+ years in AWS, Kubernetes & AI
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Cloud & DevOps Engineer with hands-on experience in AWS, Docker, Kubernetes, and CI/CD pipelines using Jenkins and GitHub Actions. Extends core DevOps skills into AI development - building multi-agent systems with Google ADK, Vertex AI, and Gemini 2.5 Flash, and RAG-based applications. Passionate about designing, automating, and monitoring production-grade cloud infrastructure.
Kammavari Sangham Institute of Technology
B.E. · Computer Science and Engineering
August 1, 2021 – June 30, 2025
RAG-Based Question Answering System
June 1, 2026 – Present
Built a Retrieval-Augmented Generation (RAG) system that ingests documents, indexes them using FAISS vector embeddings, and answers user queries with accurate, context-grounded responses using an LLM. Implemented document chunking, embedding generation, and semantic similarity search to retrieve the most relevant context before passing it to the language model - reducing hallucinations significantly. Designed a clean query pipeline connecting document retrieval and LLM generation, demonstrating practical understanding of RAG architecture used in real-world AI applications.
View ProjectAI Helpdesk Agent System
June 1, 2026 – Present
Architected an AI-powered IT helpdesk using Google ADK and Gemini 2.5 Flash with specialized sub-agents for ticket classification, troubleshooting, and escalation - enabling near-zero-touch resolution of common IT requests. Built a multi-agent orchestration layer routing tickets to domain-specific agents (network, hardware, software), significantly reducing manual triage overhead. Deployed the inference pipeline on Vertex AI for scalable, production-ready model serving with structured tool-use and function-calling patterns.
View ProjectFile & Folder Automation Agent
June 1, 2026 – Present
Built a Google ADK agent that executes create, rename, delete, and update file/folder operations via natural language, demonstrating practical agentic tool-use design. Defined custom tool schemas within the ADK framework, gaining first-principle understanding of function-calling patterns used in modern AI agent pipelines.
AWS Highly Available Web Application
June 1, 2026 – Present
Deployed a fault-tolerant web application on EC2 with an Application Load Balancer and Auto Scaling group, maintaining uptime during simulated traffic spikes and instance failures. Engineered a secure multi-tier VPC with public/private subnets, NAT Gateway, and fine-grained Security Groups, achieving full network isolation across application tiers. Implemented end-to-end observability with CloudWatch metrics, structured logs, and alarms to surface issues before they impacted end users.
AgroScan - Crop Disease Detection System
June 1, 2026 – Present
Built an ML model to detect crop diseases from leaf images using preprocessing, normalization, and data augmentation techniques to improve training data quality. Evaluated model performance using accuracy, precision, and recall metrics; iterated on the architecture to achieve optimal classification results. Implemented a scalable image processing pipeline to handle varied real-world input conditions and improve model generalisation across different crop types.
Cloud Computing Master Training
Besant Technologies
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a diverse skill set spanning traditional DevOps (AWS, Docker, Kubernetes, CI/CD) and emerging AI/MLOps (RAG, AI Agents). This breadth of interest and willingness to explore new domains suggests adaptability and a proactive learning attitude, which are positive indicators for cultural fit in an innovative environment. The academic nature of all projects, however, means real-world team collaboration and project management experience are not evident.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to design, implement, and monitor complex systems, suggesting good problem-solving and operational thinking. The focus on observability and fault tolerance in projects aligns with best practices for operational fit. However, without direct interview data, soft skills like teamwork and communication in a professional setting cannot be fully assessed.