AI Engineer with 1+ years in building and deploying production-ready AI/ML solutions, specializing i
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Computer Science graduate from SZABIST University with 1+ year of hands-on experience building and deploying production-ready AI/ML solutions. Specialized in Python, LLMs (OpenAI, Anthropic), RAG pipelines, and vector databases (Pinecone, Chroma). Proficient in backend development using FastAPI and Django, workflow automation with n8n, and cloud deployment on AWS and Vercel. Proven ability to reduce AI hallucinations, improve retrieval accuracy, and ship end-to-end intelligent systems.
SZABIST University
BS · Computer Science
N/A – June 30, 2026
H Tech
AI Engineer
September 1, 2025 – April 1, 2026
India
National Science & Technology Park
AI/ML Intern
January 1, 2025 – August 1, 2025
India
Microsoft 365 Productivity & Automation Suite
June 24, 2026 – Present
Designed and automated end-to-end business workflows using Power Automate, connecting Microsoft Forms, Outlook, Teams, and SharePoint to eliminate manual data entry and reduce processing time by 45%. Built dynamic Excel dashboards with Power Query and Pivot Tables for real-time KPI tracking, consolidating data from multiple OneDrive sources into a single reporting view. Developed professional Word report templates with automated mail-merge and structured PowerPoint decks with consistent branding for team presentations. Configured SharePoint document libraries and Teams channels for centralized collaboration, improving team file access and version control across distributed members
N8N WhatsApp Automation
June 24, 2026 – Present
Built an end-to-end WhatsApp automation workflow handling 1,000+ messages/day with AI-powered responses via WhatsApp Cloud API. Integrated LLM nodes in n8n for dynamic message routing and automated replies, reducing manual response effort by 70%. Designed modular webhook-based pipelines, cutting new workflow setup time by 60% through reusable node templates.
Bazm-e-Sukhan - AI-PoweredPoetry Platform (FYP)
June 1, 2025 – April 1, 2026
Built a full-stack AI platform integrating LLMS (OpenAI/Anthropic) for Urdu/English poetry generation and stylistic analysis, serving a corpus of 10,000+ poems. Implemented RAG pipelines with Pinecone and Chroma vector databases, achieving 90%+ retrieval accuracy for context-aware poetry search. Developed semantic search using vector embeddings, reducing average query response time by 50% compared to traditional search. Integrated OCR pipeline to digitize 500+ pages of scanned poetry books and ingest them into the AI search system.
Fake News Detection System
January 1, 2025 – January 1, 2025
Trained an NLP classification model using TF-IDF vectorization achieving 92% accuracy on a 20,000-article dataset. Built an interactive Streamlit web app enabling real-time fake news classification with sub-second response time. Applied text preprocessing, feature engineering, and 5-fold cross-validation, improving F1-score by 15% over baseline.
Customer Segmentation Using Clustering
January 1, 2025 – January 1, 2025
Applied K-Means clustering to segment customers based on purchasing behavior and demographics. Performed exploratory data analysis (EDA) and feature engineering to identify customer patterns. Generated visual insights using Matplotlib to support data-driven marketing strategies. Utilized Pandas, NumPy, and Scikit-Learn for end-to-end preprocessing, clustering, and evaluation.
AI-Powered REST API Backend
January 1, 2025 – January 1, 2025
Built production-grade REST API backends with FastAPI and Django REST Framework, supporting 10+ AI model inference endpoints with JWT authentication. Integrated LLM and PDF parsing pipelines into API routes, enabling document-based Q&A; with 85%+ answer accuracy on test datasets. Designed modular, scalable architecture reducing average API response time to under 300ms under concurrent load.
Machine Learning Specialization
Stanford / DeepLearning.AI (Andrew Ng)
January 1, 2024 – Present
AWS Generative AI Applications Professional Certificate
Amazon Web Services
January 1, 2024 – Present
AI For Everyone
DeepLearning.AI
January 1, 2024 – Present
Cultural Fit Analysis
The candidate demonstrates a strong interest in AI/ML through diverse personal and academic projects, including creative applications like the AI-Powered Poetry Platform. Their experience spans both corporate (H Tech) and research (NSTP) environments, indicating adaptability. The breadth of skills, from core AI/ML to backend development, cloud deployment, and even automation tools like n8n and Microsoft 365, suggests a versatile individual eager to learn and apply various technologies. However, the focus is heavily on AI/ML, and while valuable, a broader exposure to general software engineering practices beyond AI-specific backend development could enhance cultural fit in diverse engineering teams.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving, team collaboration (e.g., FYP, cross-functional teams at H Tech), and technical communication (e.g., generating visual insights, structured reports). The experience in automating workflows with n8n and Microsoft 365 suggests an operational mindset focused on efficiency and process improvement. The mention of Agile Development in skills further supports operational fit.