AI Engineer with less than a year in Machine Learning & Full-Stack Development
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
To secure a position as an AI/ML Developer where I can apply my skills in Machine Learning, Python, and Full-Stack development to build intelligent applications, continuously learn emerging technologies, and contribute effectively to high-impact projects in the IT industry.
GIFT AUTONOMOUS College
B.Tech · Computer Science and Engineering (AI)
August 1, 2023 – June 30, 2027
BSK College Maithon
Intermediate
N/A – May 31, 2022
Don Bosco Ramkanali Dhanbad
Matriculation
N/A – May 31, 2020
CTTC
Intern in AI/ML
May 1, 2025 – June 10, 2025
Bhubaneshwar, Odisha, India
Production-Grade Multi-Agent AI Copilot
June 15, 2026 – Present
Built an autonomous multi-agent AI system capable of dynamic task planning, tool selection, and intelligent query execution using LLM-driven orchestration. Implemented Retrieval-Augmented Generation (RAG) pipeline with PDF/DOCX document understanding, vector embeddings, FAISS retrieval, and multi-document session isolation. Integrated real-time web search, explainable AI reasoning, source attribution, and conversational memory to improve response accuracy and transparency. Designed and deployed a full-stack AI application with Fast API backend and interactive frontend interface, enabling live document upload and AI-powered querying.
Plant Disease Detection System (Full Stack + Deep Learning)
June 15, 2026 – Present
I built an end-to-end plant disease detection system using a custom CNN trained on thousands of leaf images to classify multiple crop diseases. The model focuses on learning visual patterns such as color variations, spots, and texture to accurately identify diseases. Data preprocessing and augmentation were applied to improve generalization. The trained CNN model was deployed as a real-time prediction service using FastAPI and integrated into a web application. Users can upload leaf images and receive instant disease predictions through an API-driven workflow.
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest in practical AI applications, from multi-agent systems to plant disease detection, indicating a problem-solving and innovation-driven mindset. Participation in hackathons and technical quizzes suggests a competitive spirit and willingness to engage with the tech community. The focus on AI/ML aligns well with an AI Engineer role, showing a clear career path and dedication to the field. The breadth of skills across ML, DL, and full-stack development indicates adaptability and a holistic approach to project delivery.
Soft Skills & Operational Fit
The candidate describes themselves as result-oriented, self-driven with a strong growth mindset, and an adaptive learner with strong problem-solving acumen. These traits suggest a good operational fit for dynamic AI/ML development environments. Participation in coding challenges and building personal tech projects indicates initiative and a proactive approach to learning and problem-solving.