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AI Engineer with 2+ years in Generative AI, LLM, and Full-Stack Development
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Assessing your cultural and operational fit
Computer Science student at FAST NUCES with practical experience building and evaluating AI/ML prototypes, Generative AI applications, and full-stack software solutions. Proficient in Python and its data science ecosystem (NumPy, Pandas, Scikit-learn), with hands-on experience developing intelligent solutions using LangChain, RAG pipelines, and LLM APIs. Passionate about applying AI/ML concepts to engineering challenges through collaboration, iteration, and rigorous testing.
FAST NUCES
Bachelor of Science · Computer Science
N/A – June 30, 2027
Open Source Contributor
TypeScript / Documentation
January 1, 2025 – Present
India
Freelance Developer
AI/ML & Full-Stack Python Projects
January 1, 2024 – Present
India
AI Chatbot
January 1, 2025 – Present
Prototyped a conversational AI assistant using Meta Llama 3 and LangChain for multi-turn context management. Evaluated model response quality and latency across configurations; leveraged Groq LPUs for optimized inference performance.
YouTube Video Summarizer
January 1, 2025 – Present
Built a full-stack AI application automating video transcription and summarization using OpenAI Whisper and Gemini/Groq LLMs. Applied Pandas-based data processing for transcript handling and structured content extraction from media pipelines. Developed backend APIs with FastAPI and SQLite persistence; followed software engineering best practices including modular design and API documentation.
Real-Time PDF Assistant
January 1, 2025 – Present
Developed a Generative AI prototype enabling real-time conversational querying of large PDF documents - a practical proof-of-concept for document intelligence automation. Built a complete RAG pipeline: PDF extraction, text chunking, HuggingFace sentence embeddings, and FAISS vector store with Top-K semantic retrieval. Integrated Groq LLaMA3-8B via LangChain's ConversationalRetrievalChain with session memory and page-level citations for result traceability. Iterated on the prototype through hands-on testing and debugging; delivered a Streamlit UI accessible to non-technical end users.
Cultural Fit Analysis
The candidate's involvement in personal projects and open-source contributions indicates a proactive and self-driven individual. The diversity of AI-focused projects (PDF assistant, video summarizer, chatbot) shows a broad interest within the AI domain. The freelance experience suggests an ability to work independently and deliver client-focused solutions. While the experience level is low, the demonstrated initiative aligns with a culture that values continuous learning and practical application.
Soft Skills & Operational Fit
The candidate demonstrates initiative through freelance work and open-source contributions. Project descriptions highlight an iterative approach to development and a focus on delivering practical solutions. Collaboration is mentioned in the open-source context. The candidate's coursework and project experience suggest a structured approach to problem-solving and an understanding of software development lifecycles.