AI Engineer with less than a year in Agentic AI & Machine Learning
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Asif Ali is an aspiring AI Engineer with 11 months of experience in developing and deploying AI systems. Proficient in Python, TensorFlow, PyTorch, and frameworks like LangChain and LangGraph, Asif has built innovative solutions including an AI proctoring system, an AI-powered recruitment platform, and a virtual AI doctor. With a strong foundation in computer science and practical project experience, Asif is adept at leveraging AI to automate workflows, enhance efficiency, and solve complex problems.
FAST National University of Computer and Emerging Sciences
BS · Computer Science
N/A – June 30, 2025
FAST University
Research Assistant
June 1, 2026 – Present
India
MTBC CareCloud
AI Engineer
April 1, 2025 – March 1, 2026
India
AI-Powered Recruitment System (IARS)
June 23, 2026 – Present
Built an end-to-end Agentic AI hiring pipeline automating job description generation, CV parsing, and candidate shortlisting. Designed multi-agent workflows using LangGraph for JD generation, resume parsing, scoring, and communication. Implemented semantic candidate matching using embeddings and multi-factor scoring (skills, experience, projects, GitHub). Developed automated email system for interview invitations and follow-ups using LLM-generated responses.
Virtual AI Doctor
June 23, 2026 – Present
Developed a virtual AI doctor that interacts with patients to understand their symptoms and provide basic medical advice and over the counter treatments. The agent uses symptom analysis to detect serious conditions and ensures patient safety through timely escalation. If critical symptoms are detected, it automatically refers the case to a human doctor and books an appointment. This project demonstrates the use of Agentic AI for accessible, automated, and responsive healthcare support.
AdInsight
June 23, 2026 – Present
Developed a browser extension platform for video ad analysis with modules for engagement tracking, demographic analysis, and object detection.
Agentic Online Exam Monitoring System
June 23, 2026 – Present
Designed an end-to-end AI proctoring system starting with automated face-based attendance verification. Built multi-agent pipelines for real-time monitoring including gaze tracking, head pose, body movement, multi-face detection, mobile usage, tab switching, and voice activity. Orchestrated parallel agents using LangGraph and aggregated signals for intelligent decision-making. Generated structured exam integrity reports using LLM-based reasoning from multi-modal inputs.
Cultural Fit Analysis
The candidate's academic projects showcase a diverse range of applications for AI, from recruitment to healthcare and online proctoring, indicating adaptability and a broad interest in AI's potential. The experience as an AI Engineer and Research Assistant aligns well with a research-oriented or innovative AI team. The breadth of technologies used suggests a willingness to learn and integrate new tools, which is beneficial for cultural fit in a dynamic environment. However, without more information on collaborative experiences, a deeper cultural fit analysis is limited.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to conceptualize and implement complex AI systems, suggesting strong problem-solving and analytical skills. The academic projects demonstrate initiative and a proactive approach to learning and applying advanced AI concepts. However, without direct interview data or psychometric test results, a comprehensive assessment of soft skills like teamwork, communication, and stress handling is not possible.