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AI Engineer with less than a year in Machine Learning & LLM-based Systems
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI-focused Computer Science undergraduate with hands-on experience in machine learning, data analysis, and LLM-based systems. Strong foundation in Python, statistics, and backend engineering for deploying intelligent systems. Experienced in building multi-agent AI architectures, data-driven APIs, and applied ML solutions using real-world datasets.
FAST National University of Computer and Emerging Sciences
B.S. Computer Science · Computer Science
August 1, 2022 – June 30, 2026
Ovrlod Put Limited by FAST Ventures
AI Engineer Intern
April 1, 2026 – Present
Karachi, Sindh, Pakistan
AI-Driven AdTech Analytics & Multimodal Vision Pipeline
January 1, 2026 – January 1, 2026
Engineered an automated AdTech intelligence pipeline using Python and LLMs to extract and analyze competitor campaign data. Developed a multimodal vision system utilizing OpenCV and Llama-4 to decode visual strategies from video ads.
Final Year Project – Multi-Agent AI Banking Support System
January 1, 2025 – January 1, 2026
Designed a multi-agent AI system for automated banking support with intent classification and task routing. Integrated LLM-based agents with Python and Java via REST APIs, ensuring scalability and secure data handling.
Micro-Agent Orchestrator for AI Tasks
January 1, 2025 – January 1, 2025
Developed an orchestration backend to route requests to specialized AI agents with local LLM inference. Connected Python NLP services via async REST pipelines with logging, request tracking, and secure API access.
Google AI Professional Certificate
January 1, 2026 – Present
CS50 - Artificial Intelligence with Python
Harvard University
January 1, 2025 – Present
Cultural Fit Analysis
The candidate's project diversity, including academic, personal, and internship experiences, demonstrates a broad interest in applying AI across different domains. The involvement in a leadership role (Vice President Tech at MLSA) indicates a proactive and engaged approach, which aligns well with a dynamic technical environment. The target role of AI Engineer is well-aligned with the candidate's stated interests, skills, and project work, particularly in multi-agent systems and LLM integration.
Soft Skills & Operational Fit
The candidate's leadership role as Vice President Tech at MLSA suggests initiative and potential for team collaboration. Project descriptions indicate an ability to work on complex, multi-component systems. However, without psychometric test results, a comprehensive assessment of logical reasoning, work attitude, stress handling, and team collaboration is not possible.