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AI Engineer with less than a year in AI agent development, LLM analysis, and deep learning.
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Final Year Undergraduate specializing in Computer Science and Engineering. Possessing practical experience as an AI Agent Developer, actively involved in building multi-agent AI architectures and implementing LangChain-based orchestration for complex workflows. Skilled in LLM analysis, evaluating models, and documenting generative AI applications. Led projects in AI-powered customer care systems, deep learning-based brain MRI tumor detection, and generative AI medical summary generators, leveraging Python, TensorFlow, and LangChain.
St. Martin's Engineering College, Hyderabad
B.Tech · Computer Science and Engineering + CS
August 1, 2022 – June 30, 2026
Narayana Junior College, Hyderabad
Intermediate Education
June 1, 2020 – May 31, 2022
Narayana Olympiad School Hyderabad
Secondary Education
N/A – May 31, 2020
ReGen Consult
AI Agent Developer
January 1, 2026 – March 1, 2026
India
Virtusa
Technology Intern
January 1, 2025 – April 1, 2025
India
Automobile Customer care
June 1, 2026 – Present
Architected an AI-powered Automobile Customer Care system using a RAG pipeline with LangChain agents, enabling prompt routing, conversation memory, and tool calling for intent-aware, multi-turn interactions. Implemented semantic retrieval with OpenAI Embeddings and FAISS, integrated with GPT-5-Nano for low-latency, grounded inference, reducing hallucinations and supporting scalable automation.
Deep Learning-Based Brain MRI Tumor Detection System
June 1, 2026 – Present
Designed and trained a CNN-based binary classification model for brain MRI tumor detection using TensorFlow and Keras, learning hierarchical spatial features to distinguish tumor vs. non-tumor patterns. Performed dataset curation and preprocessing on Kaggle MRI data (resizing, normalization, augmentation), trained the network over 75 epochs using backpropagation and gradient-based optimization, and deployed an inference pipeline to classify uploaded MRI images.
Gen AI-Based Medical Consultation Summary Generator
June 1, 2026 – Present
Developed an automated medical documentation system that converts doctor-patient conversations into structured clinical summaries using speech-to-text and LLM-based information extraction. Implemented entity and intent extraction to generate key medical fields such as disease, prescribed treatment, and medication names, reducing manual documentation and enabling real-time clinical decision support.
Fundamentals of Agents
Hugging Face
June 1, 2026 – Present
Introduction to LangChain (Python)
LangChain Academy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including customer care, medical imaging, and medical consultation summarization, indicates a broad interest in applying AI across different domains. Their involvement in AI agent development and LLM analysis aligns well with an AI Engineer role. The certifications further demonstrate a proactive approach to learning and staying current with AI technologies, suggesting a good fit for a dynamic, innovation-driven environment.
Soft Skills & Operational Fit
The candidate demonstrates an ability to work on complex, multi-component AI systems, as evidenced by the multi-agent architecture project. Their project descriptions suggest a problem-solving mindset and an understanding of real-world application challenges like reducing hallucinations and enabling real-time decision support. The internship experience at Virtusa also highlights an analytical and documentation-oriented approach to technology.