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Generative AI Engineer with less than a year in LLM-powered applications & full-stack Python develop
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 Engineer with hands-on expertise in building LLM-powered applications, RAG pipelines, and agentic AI systems. Proficient in designing and deploying AI solutions using GPT-based APIs, vector databases, and FastAPI backends. Complemented by a solid foundation in full-stack Python development (Django, React.js) and cloud deployment (AWS). Passionate about delivering scalable, production-ready AI products that solve real-world problems.
Sarabhai Institute of Science and Technology, Trivandrum
Master of Technology · Electronics & Communication Engineering
N/A – Present
Faith Infotech Academy, Technopark
Python Full Stack & AI Engineer Intern
January 1, 2024 – June 30, 2024
India
Smart Tech Support System with RAG
June 24, 2026 – Present
Engineered an end-to-end Technical Support System leveraging RAG-based knowledge base search powered by GPT LLM API, delivering context-aware and accurate issue resolution. Designed and managed custom text knowledge base ingestion pipeline - chunking, embedding, and indexing for high-precision semantic retrieval. Implemented OpenAI GPT API integration with token budget management, prompt engineering, and multi-LLM output evaluation for response quality benchmarking. Built role-based interfaces for Customers, Support Agents, and Admins with real-time chat interaction backed by a Django REST API and React.js frontend.
View ProjectMulti-Specialty Healthcare Management System
June 24, 2026 – Present
Architected a comprehensive clinic management platform automating patient registration, appointment scheduling, billing, and multi-role workflows (Admin, Doctor, Receptionist, Lab, Pharmacy). Designed and implemented the Lab Technician module CRUD APIs for lab test retrieval, result entry, status tracking, and integrated billing for diagnostics. Built a real-time doctor notification system triggered when lab results are published, improving care coordination. Deployed on AWS (EC2 + RDS), ensuring scalable, production-grade infrastructure.
Cultural Fit Analysis
The candidate's project diversity, including a Generative AI system and a full-stack healthcare platform, indicates a broad interest and adaptability to different problem domains. The target role of 'Generative AI Engineer' aligns well with the candidate's stated professional summary and project focus. The mention of a research paper and strong academic performance (CGPA 8.4) suggests a drive for continuous learning and contribution, which are positive indicators for cultural fit in an innovative environment.
Soft Skills & Operational Fit
The candidate's resume highlights strong analytical and problem-solving skills, adaptability, and a track record of delivering projects end-to-end. These traits suggest a good operational fit for a role requiring independent problem-solving and project ownership. The project descriptions indicate an ability to work on complex systems and manage various components.