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AI Engineer with less than a year in LLMs, RAG, & Generative AI
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final-year Computer Science student at FAST National University with a strong foundation in Artificial Intelligence, Machine Learning, and Large Language Models (LLMs). Actively developing expertise in deep learning, NLP, and Generative AI through hands-on projects. Highly motivated, fast learner, and strong communicator focused on building scalable AI systems using modern ML frameworks.
FAST National University of Computer and Emerging Sciences
Bachelor's · Computer Science (BSCS)
N/A – June 30, 2026
Forman Christian College University (FCCU)
F.Sc · Pre-Engineering
N/A – Present
KIPS Education System
Matric · Science Subjects
N/A – Present
Multi-Agent AI Assistant (LLMs + RAG)
January 1, 2026 – June 1, 2026
• Built multi-LLM AI assistant using GPT, Claude, Gemini. • Designed RAG-based pipeline using FastAPI. • Used LangChain and LangGraph for agent workflows.
AI Backend Developer Intern Project
January 1, 2026 – June 1, 2026
• Developed backend for AI therapeutic system using multiple LLMs. • Implemented RAG pipeline and API integrations. • Managed coordination and task distribution.
YouTube Q&A RAG System
January 1, 2026 – June 1, 2026
• Built Streamlit app for YouTube transcript-based Q&A. • Used Mistral-7B and MiniLM embeddings for retrieval.
LLM Fine-Tuning System
January 1, 2026 – June 1, 2026
• Fine-tuned Mistral-7B using LoRA + 4-bit quantization. • Improved performance on domain-specific datasets.
F1 Race Prediction Model
January 1, 2026 – June 1, 2026
• Built ML models using historical Formula 1 data. • Applied preprocessing and Scikit-learn algorithms.
Cultural Fit Analysis
The candidate's project portfolio demonstrates a strong interest in cutting-edge AI technologies, particularly Generative AI and LLMs, which aligns well with an AI Engineer role. The diversity of personal projects (Q&A systems, multi-agent assistants, fine-tuning, prediction models) shows initiative and a proactive learning approach. However, the lack of professional experience beyond an internship and the focus on personal projects might indicate a need for mentorship and integration into a structured team environment. The candidate is still a student, which implies a learning-oriented mindset that could be a good cultural fit for a growth-focused team.
Soft Skills & Operational Fit
The candidate lists problem-solving, leadership, and communication as soft skills. The project descriptions indicate an ability to manage coordination and task distribution (AI Backend Developer Intern Project), suggesting some operational fit. However, without direct interview data or specific examples of these skills in action, it's difficult to fully assess their depth.