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AI Engineer with less than a year in Generative AI & LLM Applications
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Computer Science Engineering graduate (2026) with a 9.09 CGPA and experience building Generative AI, LLM-powered, and AI automation applications. Skilled in Python, REST APIs, Prompt Engineering, Retrieval-Augmented Generation (RAG), AI workflow automation, and backend development. Hands-on experience integrating OpenAI, Gemini, and Groq APIs, developing intent extraction systems, and deploying production-ready AI solutions. Passionate about Agentic AI, LLM evaluation, and retrieval systems.
SRKR Engineering College
B.Tech · Computer Science & Engineering
August 1, 2022 – June 30, 2026
Narayana Group of Institutions, Rajahmundry
Intermediate (MPC)
June 1, 2020 – May 31, 2022
Narayana Group of Schools, Rajahmundry
Secondary School Certificate (SSC)
June 1, 2020 – May 31, 2020
AI Studio
Generative AI Engineer Intern
July 1, 2025 – June 1, 2026
India
AI Application Generator
January 1, 2026 – June 1, 2026
Built an AI-powered platform that converts natural language requirements into structured application specifications (AppSpec + DB schema) using LLMs. Developed an intent extraction pipeline for automated AppSpec and database schema generation using multi-LLM integration. Designed 10+ REST APIs with FastAPI and implemented structured validation using Pydantic. Containerized and deployed the application using Docker and Hugging Face Spaces for production-ready AI services.
AI-Powered Intent Extraction & Query Understanding System
January 1, 2026 – June 1, 2026
Built an AI-powered system to identify user intent and extract structured entities from natural language queries. Integrated multiple LLM providers (OpenAI, Gemini, Groq) to compare model responses and improve extraction accuracy. Designed prompt engineering workflows for intent classification, entity extraction, and structured output generation. Evaluated model outputs, analyzed edge cases, and refined prompts to improve reliability and consistency.
Drift Detection & Adaptation Using LoRA and SEAL
January 1, 2026 – June 1, 2026
Built a real-time drift detection system to identify deviations in LLM behavior and model output distributions over time. Implemented LoRA (Low-Rank Adaptation) for efficient fine-tuning and parameter-efficient adaptation of large language models. Integrated SEAL (Self-Evolving Adaptive Learning) for continuous model self-improvement and autonomous adaptation to new data distributions. Delivered a working end-to-end prototype at the Centific Hackathon, demonstrating real-time drift detection and recovery.
Cisco Python Essentials
Cisco
June 1, 2026 – Present
Google Generative AI
June 1, 2026 – Present
HackerRank Java (Basic)
HackerRank
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse personal projects and hackathon participation demonstrate initiative, a passion for AI, and a drive for continuous learning, which are strong indicators of cultural fit for an innovative AI engineering team. The focus on end-to-end solutions (from design to deployment) shows a product-oriented mindset. The academic achievements and certifications further underscore a commitment to excellence and self-improvement.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving (intent extraction, drift detection), attention to detail (evaluating model outputs, analyzing edge cases), and a proactive approach to learning new technologies (LoRA, SEAL). The hackathon participation suggests teamwork and ability to deliver under pressure. The detailed project descriptions indicate good communication of technical work.