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AI Engineer with less than a year in Machine Learning, Deep Learning, and Generative AI for end-to-e
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Assessing your cultural and operational fit
Data Science graduate (Osmania University + Innomatics Research Labs) with hands-on expertise in Python, SQL, Machine Learning, Deep Learning, and end-to-end AI system development. Proficient in building production-ready RAG applications, Computer Vision pipelines, and deploying interactive ML models via Streamlit. Strong foundation in Generative AI, LangChain, FAISS, and vector databases; actively exploring LLM evaluation, AI agents, and advanced prompt engineering for intelligent automation and data-driven solutions.
Osmania University
B.Sc. in Data Science · Data Science
N/A – June 30, 2024
Innomatics Research Labs
Data Science Program · Data Science
N/A – June 30, 2026
E-Commerce RAG Chatbot | AI Customer Support System
June 26, 2026 – Present
Designed end-to-end RAG chatbot using LangChain, FAISS, and HuggingFace embeddings to retrieve accurate insights from PDF product catalogs and live JSON order records, reducing hallucinations. Integrated Gemini 2.5 Flash with structured prompts for real-time order tracking, refund, inventory, and pricing responses; delivered production-ready Streamlit UI with secure API handling and optimized caching.
AI Website Generator | Prompt-Based Web Development System
June 26, 2026 – Present
Built a Streamlit application that converts natural language prompts into fully functional HTML/CSS/JavaScript websites via Google Gemini and LangChain, automating end-to-end frontend code generation. Engineered strict prompt formatting, parsing logic, and automated pipeline for UTF-8 encoding, file separation, and ZIP packaging - enabling one-click website generation and download.
ATS Resume Screening Automation | End-to-End HR Automation
June 26, 2026 – Present
Built automated ATS workflow using n8n to process single PDF and bulk ZIP resume submissions with fault-tolerant, scalable execution and AI-based scoring for text extraction and candidate analysis. Developed Python scripts for data cleaning, validation, and standardization; automated Accept/Reject classification via threshold logic routing results to Google Sheets, eliminating manual screening effort.
Cultural Fit Analysis
The candidate's projects demonstrate a strong alignment with an AI Engineer role, covering diverse applications like customer support, web development, and HR automation. This breadth of application, combined with continuous learning (e.g., 'Currently Exploring' section), suggests adaptability and a proactive approach to new technologies, which are positive indicators for cultural fit in an innovative AI team. The focus on practical, problem-solving applications aligns well with a results-oriented culture.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to design and implement complex AI solutions, suggesting strong problem-solving and execution skills. The focus on 'production-ready' systems and 'optimized caching' implies an understanding of operational considerations. However, without specific psychometric or communication test results, it's difficult to assess soft skills like teamwork, stress handling, or direct communication clarity.