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Generative AI Engineer with less than a year in Generative AI, LLMs, and RAG Systems for intelligent
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI/ML Engineer focused on Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Natural Language Processing, and Agentic AI Systems. Experienced in building intelligent document retrieval platforms, semantic search applications, AI-powered assistants, and production-oriented machine learning solutions. Strong background in LangChain, vector databases, FastAPI, transformer-based architectures, experimentation, model evaluation, and scalable AI system design.
Integral University
Bachelor of Technology (B.Tech) · Computer Science Engineering
N/A – Present
Invoice Information Extraction
June 1, 2026 – Present
Combined OCR and LLM-based validation for invoice and financial document processing. Improved field extraction accuracy by 30%. Reduced malformed outputs by 40% using schema-constrained generation. Added confidence scoring mechanisms to improve parsing reliability.
Legal Research Assistant
June 1, 2026 – Present
Engineered a retrieval-augmented generation system for legal document analysis and information retrieval. Improved citation accuracy by 25% using query rewriting, context compression, and reranking. Reduced context noise by 40% through optimized retrieval strategies. Developed ReAct-style agent workflows for multi-step reasoning and tool usage.
Financial Document Intelligence System
June 1, 2026 – Present
Automated extraction of KPIs such as revenue trends and EBITDA from financial reports. Reduced hallucinated outputs by 38% using output guardrails and structured generation. Studied vector retrieval techniques, semantic search, and contextual reasoning systems. Conducted benchmarking and performance analysis of modern AI workflows.
View ProjectJobHunt Bot - Resume Intelligence System
June 1, 2026 – Present
Designed an end-to-end platform for matching resumes with job descriptions using semantic similarity. Improved recommendation relevance by 28%. Generated ATS-oriented feedback and structured skill-gap analysis. Reduced manual resume review effort by 35%.
Generative AI with Transformers
DeepLearning.AI
January 1, 2024 – Present
AWS Machine Learning Foundations
Udacity
January 1, 2023 – Present
Computer Vision with PyTorch
Udemy
January 1, 2023 – Present
Cultural Fit Analysis
The candidate's portfolio of personal projects demonstrates initiative, self-learning, and a strong passion for Generative AI and its applications. The diversity of projects (legal, HR, finance) shows a broad interest in applying AI to different domains. Participation in machine learning competitions and applied AI research indicates a proactive and curious mindset, which aligns well with an innovative and growth-oriented culture. The certifications further underscore a commitment to continuous learning. The lack of professional experience makes it challenging to assess cultural fit in a corporate setting fully.
Soft Skills & Operational Fit
The candidate's project descriptions indicate a problem-solving mindset and an ability to translate business problems into AI solutions. The focus on quantifiable improvements (e.g., 25% improved citation accuracy) suggests a results-oriented approach. The mention of developing 'end-to-end platforms' and 'ReAct-style agent workflows' implies an understanding of system integration and complex AI architectures. However, without direct work experience, it's difficult to assess collaboration, stress handling, or direct operational fit in a team environment.