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AI Engineer with less than a year in Backend and AI Systems
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Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Passionate Software Engineer specializing in backend and AI-integrated systems. Experienced in building scalable REST APIs, intelligent document retrieval pipelines, and modern web applications. Skilled in Node.js, React, MongoDB, Redis, and LangChain with a strong focus on clean architecture, automation, and performance-driven development.
Deogiri Institute of Engineering and Management Studies, Aurangabad.
Bachelor of Technology · Computer Science Engineering (AIML)
August 1, 2022 – June 30, 2025
Marathwada Institute of Technology, Aurangabad.
Diploma · Computer Engineering
August 1, 2019 – June 30, 2022
CleverPe
Associate Software Engineer Intern
December 1, 2024 – June 1, 2025
Bengaluru, Karnataka, India
VidTube - YouTube-like Video Streaming Platform (Fullstack)
January 1, 2024 – December 31, 2024
Built a YouTube-style platform enabling users to upload videos, manage channels, watch content, like/dislike, and comment. Developed backend REST APIs for authentication (JWT), video handling, subscriptions, and content management. Integrated Cloudinary for secure image/video storage and smooth media streaming. Tech Stack: Node.js (Express), MongoDB, React, Vite, Tailwind CSS
Semantic Doc Search – AI-powered Documentation Retrieval
January 1, 2024 – December 31, 2024
Developed a Retrieval-Augmented Generation (RAG) pipeline enabling semantic question-answering over uploaded PDF documents. Integrated LangChain workflows for embedding generation, document chunking, and context-aware responses using LLMs. Tech Stack: LangChain, Qdrant Vector DB, OpenAI Embeddings, Python
AI Research Paper Assistant – Generative AI-based Research Paper Summarizer
January 1, 2024 – December 31, 2024
Developed an AI-powered assistant that summarizes and explains top AI research papers like Attention Is All You Need, BERT, and GPT-3. Implemented LangChain pipelines for document parsing, context retrieval, and dynamic summarization using Google Generative Models. Built an interactive Streamlit web interface allowing users to select papers, choose summary tone & length, and view AI-generated insights. Tech Stack: LangChain, Google Generative AI, Streamlit, Python
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in AI and full-stack development, indicating a proactive and self-driven learning approach. The diversity of projects (full-stack video platform, semantic search, AI summarizer) suggests adaptability and a broad technical curiosity. The target role of 'AI Engineer' aligns well with the candidate's recent project focus on LangChain, RAG, and LLMs. However, the lack of team-based project experience or explicit collaboration details limits the assessment of cultural fit in a team environment.
Soft Skills & Operational Fit
The candidate's project descriptions suggest an ability to work independently on complex systems. The internship experience indicates exposure to professional development practices like API development and CI/CD, implying a foundational understanding of operational workflows. However, without direct assessment data, specific soft skills like teamwork or stress handling cannot be definitively evaluated.