AI Engineer with less than a year in Python & Backend Development
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Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Final-year B.Tech Computer Science (IoT) student with expertise in Python, FastAPI, and backend development, complemented by hands-on experience in machine learning and AI applications. Built scalable REST APIs, real-time processing systems, and intelligent automation solutions through academic and project work. Seeking opportunities to contribute to backend and AI-driven product development while continuously expanding expertise in Generative AI technologies.
B. S. Abdur Rahman Crescent Institute of Science and Technology
B.Tech · Computer Science and Engineering (Internet of Things)
August 1, 2022 – June 30, 2026
Vidhya Sagar Global School
Higher Secondary Education
June 1, 2020 – May 31, 2022
Chelliamman Engineering Works
IoT Test Intern
June 1, 2025 – July 31, 2025
Tamil Nadu, India
Proflo Business Intelligence
Front-end Developer Intern
December 1, 2024 – January 31, 2025
India
AI Desktop Assistant for System Automation
June 26, 2026 – Present
Built an AI-powered desktop automation system enabling natural language-based execution of local system tasks and workflow automation. Developed FastAPI backend services for command routing, file operations, process execution, and backend orchestration. Implemented lightweight automation pipelines integrating Linux/Windows command execution and real-time task handling. Containerized backend services using Docker for isolated deployment and environment consistency. Designed REST APIs and session management workflows using React and SQLite for interactive task execution.
Federated Learning based Secure IoT Communication System
June 26, 2026 – Present
Designed decentralized learning across 15+ simulated IoT nodes for secure model training without centralized data storage. Built LSTM-based threat prediction achieving 87% detection accuracy on test traffic datasets. Reduced routing latency by 22% using genetic algorithm-based path optimization. Implemented Python-based distributed training and inference pipelines for decentralized model updates.
Real-time Crowd Risk Detection using Computer Vision
June 26, 2026 – Present
Processed video feeds at 20 FPS to identify crowd density and potential risk zones in real time. Achieved 90% accuracy in crowd detection using YOLOv8 and CSRNet models. Generated evacuation paths reducing estimated exit time by 30% using Dijkstra's algorithm. Designed REST APIs using Flask for real-time data processing and client-server communication. Built real-time inference pipeline integrating detection models with backend processing workflows.
Cultural Fit Analysis
The candidate's academic projects demonstrate a strong interest and capability in AI/ML, which aligns well with an AI Engineer role. The diversity of projects (desktop automation, federated learning, computer vision) shows a broad technical curiosity. However, the experience is primarily academic, and the internships are not directly in AI engineering, which might require some ramp-up in a professional AI team environment. The candidate is still pursuing a B.Tech degree, indicating a junior-to-mid-level fit for a senior role, but with high potential.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex, multi-faceted problems, suggesting good problem-solving skills. The internships, though short, show exposure to real-world testing and development cycles. The academic nature of most projects means practical operational experience in a corporate setting is limited. The candidate's summary mentions seeking opportunities to expand expertise in Generative AI, indicating a proactive learning attitude.