AI Automation Engineer with less than a year in Agentic AI & LLM Integration
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AI Automation Engineer specializing in Agentic AI, LLMs, GenAI, RAG systems and intelligent workflow automation. Experienced in prompt engineering, API integration and end-to-end ML pipelines with Python, Scikit-learn and Pandas passionate about building smart, production-ready AI systems.
COMSATS University Islamabad
BS Computer Science · Computer Science
August 1, 2021 – June 30, 2025
MorpheLabs
AI Automation Engineer
April 1, 2026 – Present
India
DocQA – RAG Chatbot
June 6, 2026 – Present
• Built a RAG pipeline using FastAPI, LangChain and ChromaDB with HuggingFace sentence embeddings (all-MiniLM-L6-v2) for semantic indexing and retrieval across multi-topic PDF collections with PyMuPDF handling PDF parsing and document chunking. • Implemented a Self-RAG agentic loop with automatic query rewriting — reformulates user queries using conversation history into standalone questions, applies answer quality reflection and falls back to DuckDuckGo web search when retrieved context is insufficient. • Integrated Groq API with Llama 3.1 8B for text generation and Llama 4 Scout vision model for extracting and describing embedded PDF images, enabling multimodal document understanding. • Designed a multi-document retrieval system with source attribution — answers cite exact filename and page number with confidence scoring based on retrieval quality.
View ProjectChatClub, MERN Stack Real-Time Chat & Video Calling App
June 6, 2026 – Present
• Built a full-stack MERN chat and video calling app where language learners connect with native speakers for real-time practice. • Integrated Stream Chat SDK for real-time messaging with emoji reactions, file/image sharing, and unread message badges. • Implemented one-on-one video calls with screen sharing and in-call reactions via Stream Video SDK. • Built JWT authentication with bcryptjs, protected routes and a profile-based onboarding flow. • Managed client state with Zustand and server data fetching with TanStack Query for performant UX. • Deployed on Railway with separate frontend and backend environments.
View ProjectCultural Fit Analysis
The candidate's projects demonstrate a diverse skill set, ranging from advanced AI/ML applications (DocQA) to full-stack web development (ChatClub). The current role as an AI Automation Engineer at MorpheLabs directly aligns with the target role, indicating a clear career path and interest in the domain. The breadth of technologies used and the ambition of the projects suggest a proactive and adaptable individual, which generally contributes to a positive cultural fit.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to translate complex technical requirements into functional solutions. The experience at MorpheLabs as an AI Automation Engineer aligns well with the target role, suggesting a practical, results-oriented approach to problem-solving. The focus on reducing manual effort and optimizing AI systems points to a good operational fit.