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Generative AI Engineer with 1+ years in LLMs, RAG, and Cloud Deployment
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Generative AI Developer Associate and Computer Science Engineer (2025) with hands-on experience designing AI-powered applications using LLMs, prompt engineering, and RAG pipelines. Skilled in integrating ML models into production-ready systems with Python, Spring Boot, and RESTful APIs. Proficient in vector databases, AI agent workflows, model fine-tuning, and cloud deployment. Experienced in Agile/Scrum environments, committed to building clean, scalable, and impactful intelligent solutions
Anna University
Bachelor of Engineering (B.E.) · Computer Science and Engineering
August 1, 2021 – June 30, 2025
QSpiders Institute
Generative AI Developer Trainee
January 1, 2025 – Present
Chennai, Tamil Nadu, India
Emotion-Based Movie Recommendation System
January 1, 2025 – June 1, 2026
Architected a full stack AI application detecting user emotions via webcam/image upload using a deep learning model, mapping results to personalized movie genre recommendations. Integrated LLM-based natural language generation to produce human-readable recommendation explanations, enhancing user engagement. Built and tested secure RESTful APIs following MVC architecture; documented all endpoints with Postman request/response schemas
Java Full Stack Development
QSpiders Institute
June 1, 2026 – Present
Generative AI Fundamentals
IBM
June 1, 2026 – Present
Python for Data Science & AI
IBM / Coursera
June 1, 2026 – Present
AWS Certified Machine Learning - Specialty
Google Cloud
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, including an academic project and an internship role, shows initiative and a breadth of technical interests. The focus on Generative AI and related technologies aligns well with the target role. The certifications in Generative AI, AWS ML, and Python for Data Science further demonstrate a proactive approach to skill development relevant to the AI/ML domain. However, the experience is primarily academic and internship-based, which might limit exposure to diverse corporate cultures or complex team dynamics.
Soft Skills & Operational Fit
The candidate's resume highlights experience in Agile/Scrum environments and a commitment to building scalable solutions, indicating a good operational fit for modern development teams. The project descriptions suggest an ability to work on end-to-end solutions, from model integration to API development and documentation. However, without specific behavioral assessment data, soft skills like teamwork, problem-solving under pressure, and communication clarity in a team setting cannot be fully assessed.