AI Engineer with less than a year in Generative AI and RAG pipelines.
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Assessing your cultural and operational fit
AI/ML Engineer specializing in Generative AI and RAG pipelines, with hands-on experience deploying LLM-powered applications using LangChain and FastAPI. Proven track record in automating data interpretation and building scalable intelligent solutions to drive business innovation.
Vaagdevi Engineering College, Warangal
Bachelor of Technology · Computer Science (AI&ML)
September 1, 2021 – April 1, 2025
Defence Electronics Research Laboratory (DLRL, DRDO)
Project Intern
June 1, 2025 – July 1, 2025
Hyderābād, Telangana, India
Automated Job Scraper & Telegram Notifier
August 1, 2025 – June 1, 2026
Architected a Python-based scraper to aggregate fresher-level tech job postings from multiple Indian portals. Automated real-time notifications via Telegram, featuring hourly regional updates and daily national summaries.
Strict Technical RAG Assistant
August 1, 2025 – June 1, 2026
Engineered a High-Accuracy RAG Pipeline using LangChain and Python to eliminate AI hallucinations by grounding model responses in local PDFs and live URLs. Optimized Performance & Cost by implementing HuggingFace local embeddings and FAISS vector search, enabling high-speed semantic retrieval without API overhead. Deployed a Verifiable AI Interface via Streamlit that synthesizes multi-source data with real-time source tracking for 100% transparent and auditable answers.
Certificate of Project Completion (AI/ML)
Defence Electronics Research Laboratory (DLRL, DRDO)
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in practical AI applications, from job scraping to advanced RAG systems. The internship at DRDO and the focus on 'defense-grade' RAG pipelines suggest an alignment with roles requiring robust, high-integrity solutions. The breadth of tools and platforms (Python, SQL, LangChain, FastAPI, Docker, Git, Streamlit) indicates adaptability and a willingness to explore new technologies, which is beneficial for dynamic AI engineering environments. The personal projects show initiative and a problem-solving mindset.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work independently on complex technical challenges, focusing on practical solutions like hallucination reduction and performance optimization. The 'Strict Technical RAG Assistant' project highlights a methodical approach to verifiable AI. The 'Scrum Master' achievement suggests an understanding of agile methodologies and potential for team coordination, though direct evidence of collaboration or stress handling is not provided.