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AI Engineer with 1+ years in Generative AI & LLM Integration
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Backend Engineer specializing in Generative AI and LLM integration, with experience delivering 3+ AI-powered applications including RAG systems, HR chatbots, and document QA tools. Proficient in Python, FastAPI, LangChain, Pinecone, and multi-LLM API integration focused on shipping intelligent backends that solve real problems.
DES Junior College
Class XII
N/A – May 31, 2020
Sanjivani College of Engineering
B-Tech
N/A – June 30, 2024
Laxmi Vidyalay School
Class X
N/A – May 31, 2018
Baarez technology solutions
AI Backend Engineer
March 1, 2026 – Present
India
Tech Amica
Python Developer(GenAI)
June 1, 2025 – February 1, 2026
India
HRHelper - Employee FAQ Chatbot
June 5, 2026 – Present
Built a Slack-integrated HR chatbot with a Flask backend and a JSON-based FAQ system to automate employee queries. Enabled real-time responses using the Slack SDK and exposed the backend via ngrok for seamless Slack integration. Built a web interface using HTML, CSS, and JavaScript for HR FAQ access.
Intelligent Conversational AI Agent with RAG
June 5, 2026 – Present
Developed an intelligent conversational chatbot using Python and LangChain to answer user queries by searching a knowledge base and performing real-time web retrieval. Built a scalable REST API with FastAPI to handle multiple concurrent users and maintain conversation memory. Implemented semantic search using Pinecone and Hugging Face embeddings for accurate information retrieval. Integrated Groq's Llama 3.3 LLM for natural language understanding and response generation.
View ProjectAI-Powered Document Question-Answering System using RAG
June 5, 2026 – Present
Built RAG PDF QA system with LangChain, Pinecone vector DB, and Llama 3.3, achieving 95 percent + accuracy. Integrated Groq API for LLM responses, optimizing retrieval with top-4 similarity and 1000-char chunks. Developed Streamlit web app and CLI with error handling, automated setup, and comprehensive docs. Orchestrated ML pipeline using Python, HuggingFace embeddings, and RetrievalQA chains end-to-end. Designed scalable architecture eliminating AI hallucination, handling millions of vectors in Pinecone.
Cultural Fit Analysis
The candidate's projects demonstrate a focus on practical, problem-solving AI applications, which aligns with a results-oriented culture. The experience is primarily in AI/GenAI backend roles, indicating a clear career path. However, the limited diversity in project types (mostly RAG/chatbot) and the relatively short professional experience (starting June 2025, with current role starting March 2026) suggest a need for broader exposure to different problem domains and team structures to fully assess cultural fit.
Soft Skills & Operational Fit
The candidate lists 'Adaptability', 'Critical Thinker', 'Communication', 'Leadership', 'Presentation', and 'Problem Solving' as soft skills. The project descriptions indicate problem-solving and communication through building user-facing applications. However, without specific examples or interview data, the depth of these soft skills and operational fit cannot be fully assessed.