Part II. — Career Objective
AI Software Engineer with hands-on experience in building Generative AI applications, including RAG pipelines and agentic workflows. Skilled in developing scalable, production-ready systems using modern backend technologies and AI frameworks, with a focus on solving real-world problems through intelligent and efficient solutions.
Part III. — Technical Skills
Core CS
Data Structures & AlgorithmsOOPSDBMSOperating Systems
Programming Languages
PythonJAVASQLJavaScriptHTMLCSS
Generative AI
RAG PipelinesPrompt EngineeringLLM IntegrationEmbedding ModelsTransformersChunking & Retrieval TuningMachine LearningDeep Learning
Frontend & Backend
React.js (Vite)Next.jsFastAPIREST APIsStyled-ComponentsFramer MotionCORS Configuration
Cloud & Deployment
AWS (EC2, S3, IAM, Amazon Connect)VercelRenderDocker
Database & Vector Search
MySQLFirebaseNeo4j (Graph DB)Vector Databases (FAISS, Chroma)
Web Platforms & Tools
GitGitHubWix StudioFigma
AI Frameworks & Automation
n8nMakeLangChain
Part IV. — Work Experience
AI Intern
Celerinn Technologies
10/2025 - Present
- Built and deployed Altaric, a production-grade AI-focused corporate website, delivering a complete full-stack solution.
- Built a Supplier Risk Intelligence Dashboard using FastAPI, React, and Neo4j to model supplier relationships as graph data and generate real-time risk insights with the help of Celery workers and Redis.
- Worked on ECO supporting change management processes integrating system-level updates within enterprise PLM environments using AI.
Part V. — Projects
TEASER - RAG-AGENT
- Developed a production-grade Agentic RAG platform using FastAPI, React, FAISS, LLM APIs, structured tool calling, and MCP orchestration. Improved retrieval accuracy by 35%
- Designed an end-to-end RAG pipeline with document ingestion, chunking, embeddings, similarity search, session memory, and adaptive fallback logic.
- Enabled multi-step agent workflows, dynamic tool execution, streaming responses, citation tracking, and deployed on Vercel and Render.
Online Examination Portal
- Built a full-stack application in WixStudio with analytics, performance optimization, and real-time evaluation.
- Reduced system latency by 40% through query optimization and efficient data access.
- Designed scalable result analytics and leaderboard systems.
Cross - Modal Similarity Evaluation System
- Implemented a multimodal similarity evaluation framework for text, image, audio, and video using deep learning embeddings (MiniLM, CLIP, Wav2Vec2) to compute cross-modal semantic similarity.
- Orchestrated embedding pipelines, normalization strategies, cosine similarity scoring, and model comparison across 4-6 architectures per modality.
- Designed evaluation metrics, ranking logic, and interactive visualization dashboards to benchmark performance, analyze similarity distributions, and compare model effectiveness.
Part VI. — Education & Certifications
Education
B-Tech, Artificial Intelligence
VIDYA JYOTHI INSTITUTE OF TECHNOLOGY
Current CGPA - 8.80 (till 7th semester)
2022 – 2026
Intermediate
SRI CHAITANYA JUNIOR COLLEGE
Percentage - 92.2%
2020 – 2022
Class X
SRI CHAITANYA TECHNO SCHOOL
GPA - 10.0
2020
Certifications
- DSA with JAVA (Apna College - 11/2024)
- IBM Python (05/2023)
- CISCO Networking Academy C language (Cisco - 04/2023)
- PowerBI (07/2023)
Organizations & Hobbies
TEDxVJIT
Core Team Member - Hospitality & Management
Hobbies
DanceContent WritingPoetryCricketNature Photography