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AI Engineer with less than a year in Generative AI & NLP
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AI Engineering Intern with expertise in building production-grade Retrieval-Augmented Generation (RAG) agents and multi-modal AI pipelines. Proficient in Python, FastAPI, React.js, and machine learning frameworks like LangChain and LangGraph, with a strong focus on natural language processing and computer vision applications.
Ghulam Ishaq Khan Institute of Engineering Sciences and Technology
Bachelor of Science · Artificial Intelligence
N/A – June 30, 2026
PetalNex
Artificial Intelligence Engineering Intern
June 1, 2025 – August 31, 2025
India
EduQ Semantic Exam Search Platform
January 1, 2026 – May 31, 2026
Architected a full-stack semantic search platform: Next.js App Router (TypeScript, React 19) connected to a FastAPI microservice containerized in Docker and deployed to Hugging Face Spaces, with complete ownership from development to production. Implemented multimodal vector search using OpenCLIP (ViT-B-32) embeddings in Supabase pgvector and an LLM-powered ingestion pipeline (Llama 3.3, Groq) for automated question classification, applying Computer Vision and Natural Language Processing (NLP).
Teach Back
September 1, 2025 – May 31, 2026
Architected a full-stack AI educational platform with a React.js frontend and FastAPI backend delivering token-by-token NDJSON streaming responses with Firebase authentication, supporting 50+ concurrent connections. Built a Multi-Modal Retrieval-Augmented Generation (RAG) pipeline using ChromaDB to unify PDFs (Unstructured.io + Tesseract OCR), audio lectures (Whisper), and YouTube videos (yt-dlp), with async background ingestion reducing perceived latency by 40%.
Agentic Research Assistant
January 1, 2025 – May 31, 2025
Built an autonomous agentic workflow using a LangGraph multi-agent pipeline connected to the Gmail API to read, route, and summarize emails into structured daily digest reports, saving 5+ hours/week at <2s latency. Deployed a Grafana + Prometheus monitoring stack to track agent execution health, API error rates, and pipeline throughput, providing real-time observability into the multi-agent system.
Real-Time Face Recognition Attendance System
August 1, 2024 – December 31, 2024
Designed a two-stage Computer Vision pipeline using YOLOv11: a detection model crops individual faces, then a custom-trained classification model identifies each person, achieving >30 FPS inference and 95%+ accuracy on standard CPU hardware. Deployed a Flask web portal with OpenCV integration where instructors upload a class photo and receive a live attendance dashboard; optimized input tensors to 128×128 pixels to reduce computational load.
Generative AI Engineering with LLMs
IBM
June 1, 2025 – Present
Introduction to LangGraph
LangChain Academy
June 1, 2025 – Present
Generative AI for Software Developers Specialization
IBM
May 1, 2025 – Present
IBM AI Developer Professional Certificate
IBM
May 1, 2025 – Present
ChatGPT Prompt Engineering for Developers
DeepLearning.AI
February 1, 2025 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from academic to personal initiatives, showcases a broad interest in AI applications and a self-driven learning approach. Their involvement in full-stack development and MLOps indicates a holistic view of software development, which aligns well with roles requiring versatile engineers. The focus on practical, impactful solutions (e.g., reducing manual triage time, saving hours/week) suggests a results-oriented mindset.
Soft Skills & Operational Fit
The candidate demonstrates strong initiative and problem-solving skills through their diverse project portfolio, tackling complex challenges like multi-modal RAG and real-time face recognition. Their experience with monitoring tools (Grafana, Prometheus) suggests an understanding of operational excellence and system observability. The descriptions indicate a capacity for end-to-end ownership, from development to deployment.