AI Engineer with less than a year in GenAI & Backend Development
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Assessing your cultural and operational fit
Computer Science Engineering graduate with hands-on experience designing and deploying production-ready GenAI pipelines, backend architectures, and Natural Language Processing (NLP) solutions. Demonstrated success in building scalable RAG systems, deploying high-accuracy transcription engines using Flask and Hugging Face, and engineering automation frameworks that reduce data preprocessing times by 60%. Highly proficient in full-lifecycle Python development, RESTful APIs, and relational databases.
Krishna Engineering College, Ghaziabad
B.Tech · Computer Science & Engineering
August 1, 2021 – June 30, 2024
Aditya Institute of Technology, Delhi
Diploma (Polytechnic) · ITES&M
August 1, 2016 – June 30, 2019
Eoxs
AI Intern
August 1, 2025 – September 1, 2025
India
Tech Explica
Machine Learning Intern (Python & ML)
January 1, 2019 – April 1, 2019
India
AI Portfolio Assistant (RAG)
June 1, 2026 – Present
Built an end-to-end RAG pipeline using LangChain and ChromaDB to chunk, embed, and index unstructured PDF data. Integrated Gemini API to process natural language queries regarding skills and project experience with high context accuracy. Deployed a live interactive UI via Streamlit Cloud using secure environment secret management for API access keys.
View ProjectAI Transcriptor (Flask, NLP, Python)
June 1, 2026 – Present
Developed a RESTful API with Flask and Hugging Face to achieve 95% text analysis accuracy. Optimized data pipelines for real-time audio-to-text processing and model inference.
View ProjectMovie Recommendation System (Python, Scikit-learn, Streamlit)
June 1, 2026 – Present
Implemented a content-based engine using Cosine Similarity and Scikit-learn on TMDB datasets. Deployed an interactive interface using Streamlit to visualize personalized recommendations.
View ProjectAutoEDA (Python, Pandas, Numpy)
June 1, 2026 – Present
Built an automated EDA framework using Pandas and NumPy that reduced preprocessing time by 60%. Designed modular scripts for automated feature engineering and data validation across diverse datasets.
View ProjectSupervised Machine Learning: Classification & Regression
IBM
June 1, 2026 – Present
Python Programming Fundamentals
Microsoft
June 1, 2026 – Present
Python 101 for Data Science
Cognitive Class
June 1, 2026 – Present
Data Visualization: Empowering Business with Effective Insights
TCS
June 1, 2026 – Present
Data Science & Analytics
HP LIFE
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest and initiative in AI/ML, with diverse applications from RAG systems to recommendation engines and automated EDA. This breadth of personal projects, combined with internships in AI and ML, suggests a proactive and self-driven individual who is passionate about the field. The alignment of their skills (GenAI, NLP, ML, Python) with the target AI Engineer role indicates a good cultural fit for a technically driven AI team. The candidate's educational background in Computer Science & Engineering further supports this fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on end-to-end solutions, from data processing to deployment. The focus on optimizing data pipelines and improving model performance suggests a results-oriented approach. The use of Streamlit for interactive UIs implies an understanding of presenting solutions. However, without direct assessment data, specific soft skills like teamwork, problem-solving under pressure, or communication in a team setting cannot be definitively evaluated.