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Entry-Level AI Engineer with Generative AI and RAG pipeline expertise
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Assessing your cultural and operational fit
Fresher AI Engineer with hands-on expertise in building Generative AI applications, RAG pipelines, and LLM-powered agents using Python, LangChain, and OpenAI/Gemini APIs. Experienced in deploying end-to-end AI systems with FastAPI and Streamlit. Passionate about agentic AI and transforming real-world problems into scalable, production-ready solutions.
Government Engineering College, Rewa
B.Tech · Computer Science & Engineering
August 1, 2022 – June 30, 2026
DocuMind – Multi-Agent Document Q&A System
June 24, 2026 – Present
Built a production-grade RAG system enabling natural language Q&A over PDFs, DOCX, CSV, and XLSX files with source-cited responses and page-level attribution. Implemented hybrid search (dense + BM25 sparse retrieval) using LangGraph multi-step agent, improving retrieval accuracy by 35% over standard vector search. Added confidence scoring layer to flag low-certainty answers; deployed on Hugging Face Spaces with 300-page document processing in under 12 seconds. Evaluated system on 200 custom Q&A pairs achieving 88% retrieval precision; full pipeline traced via LangSmith.
HireIQ – AI Resume Screener & Mock Interview Agent
June 24, 2026 – Present
Designed a 3-agent CrewAI system (Screener, Question Generator, Evaluator) that scores resumes against JDs and generates structured JSON feedback in under 8 seconds. Integrated Groq API (Llama 3.1) for real-time mock interview responses with ElevenLabs TTS; validated on 50 resumes with 92% evaluator relevance rating.
StockSense – Financial RAG Agent with Live Data
June 24, 2026 – Present
Built an agentic financial research assistant using tool-calling to fetch live news, query a 10,000+ document FAISS knowledge base, and generate cited Buy/Hold/Sell briefs. Implemented token-aware memory management and LLM-as-judge evaluation scoring 4.2/5 on coherence and citation accuracy across 100 test queries.
IBM AI Fundamentals
IBM SkillsBuild
June 1, 2026 – Present
Google Generative AI Learning Path
Google Cloud Skills Boost
June 1, 2026 – Present
Kaggle: Python + Intro to ML + NLP
Kaggle
June 1, 2026 – Present
Anthropic Academy - Prompt Engineering for Developers
Anthropic Academy
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and alignment with the target role of an AI Engineer, particularly in agentic AI and RAG systems. The diversity of projects (document Q&A, resume screening, financial analysis) shows a broad application of AI skills. However, the lack of professional experience and a purely academic background might indicate a need for mentorship in a corporate environment. The certifications further reinforce a commitment to continuous learning in the AI domain.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a proactive approach to problem-solving and a focus on practical, deployable solutions. The use of evaluation metrics (e.g., 88% retrieval precision, 92% evaluator relevance, 4.2/5 coherence) suggests an analytical mindset and attention to detail. However, without direct work experience, it's difficult to assess collaboration, stress handling, or direct communication skills in a professional setting.