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AI Engineer with 1+ years in Generative AI & LLM Systems
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Assessing your cultural and operational fit
AI/ML Engineer specializing in Generative AI, LLM systems, and Agentic AI, with experience building production-ready AI applications. Proficient in designing RAG pipelines, multi-agent architectures, and multimodal AI systems using PyTorch, Transformers, LangChain, and LangGraph. Experienced in deploying scalable, low-latency solutions using FastAPI, Docker, and vector databases (FAISS, Chroma). Strong focus on performance optimization, real-time inference, and end-to-end AI system development.
Chhattisgarh Swami Vivekanand Technical University (CSVTU)
B.Tech (Honors) · Computer Science and Engineering (Data Science)
August 1, 2022 – Present
Tulsi Vidya Niketan (CBSE)
Senior Secondary · Class XII
June 1, 2021 – May 31, 2021
Dept. of Computer Science, NIT Rourkela
AI/ML Research Inter
January 1, 2025 – December 1, 2025
India
Dept. of Computer Science, MNIT Jaipur
Research Intern (Software)
January 1, 2024 – June 1, 2024
India
LLM-RAG Function Execution Agent
June 1, 2025 – Present
Built a production-ready RAG-based LLM system to execute functions from natural language queries, improving response accuracy and reducing hallucinations by 25%. Designed semantic retrieval pipelines using FAISS and LangChain for efficient context-aware responses. Developed modular agent architecture supporting tool-use, memory, and structured outputs. Deployed scalable inference pipelines using FastAPI and Docker for low-latency performance.
View ProjectAI Math Mentor - Agentic Multimodal AI System
June 1, 2025 – Present
Developed a multimodal agentic AI system capable of solving mathematical problems from text, image, and voice inputs using LLM reasoning. Engineered a LangChain + LangGraph workflow integrating OCR, symbolic computation (SymPy), and vector memory (ChromaDB). Deployed a real-time interactive application on Streamlit Cloud enabling end-to-end problem solving. Improved user interaction by enabling contextual query reuse through memory-based retrieval.
View Project4-Star Rating in Python and SQL on HackerRank.
HackerRank
June 1, 2026 – Present
Certified in MATLAB and Power BI (Data Analysis & Visualization).
Unknown
June 1, 2026 – Present
Completed Android App Development Bootcamp (ISEA – MNIT Jaipur).
ISEA – MNIT Jaipur
June 1, 2026 – Present
Workshop: Applications of AI/ML in Medical Imaging.
Unknown
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and internships demonstrate a strong interest and initiative in cutting-edge AI/ML fields, aligning well with an innovative and research-oriented culture. The diversity of projects (RAG agents, multimodal math mentor, GNN-based recommender) shows a broad technical curiosity. However, the experience level is low, which might require more mentorship in a fast-paced production environment.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, end-to-end systems and a focus on performance optimization and problem-solving. The academic internships suggest an aptitude for research and development. However, without direct interview data or psychometric test results, it's difficult to fully assess soft skills like teamwork, communication, or stress handling.