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AI Engineer with 1+ years in Machine Learning & LLMs.
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Assessing your cultural and operational fit
AI Engineer with 1+ year of hands-on experience developing AI-powered applications and backend systems using Python and FastAPI. Skilled in Machine Learning, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG), with experience building solutions for intelligent document processing, semantic search, and workflow automation. Strong foundation in software engineering, API development, and problem-solving, with practical experience delivering reliable and scalable applications. Passionate about leveraging AI and modern software technologies to solve real-world business challenges.
St. Joseph's Institute of Technology
B.Tech · Artificial Intelligence and Data Science
August 1, 2022 – June 30, 2026
Introlligent
AI Engineer Trainee
June 1, 2025 – Present
Chennai, Tamil Nadu, India
CDW
Gen AI Step-Intern
January 1, 2025 – February 1, 2025
Chennai, Tamil Nadu, India
NEPHELE 2.0—AI & Cloud-Based Intelligent Robot
June 1, 2026 – Present
Integrated LLaMA via AWS Bedrock with Amazon Polly & Transcribe for voice-driven human-robot interaction, enabling full natural language control with sub-second response latency. Shipped a GenAI-powered ATS Resume Parser and Automated Lecture Module with PPT narration capabilities, reducing manual processing time. Engineered an OpenCV-based Selfie Module with S3 storage and SES email delivery for automated event-triggered image capture and management.
View ProjectArise-AI-Powered HR Recruitment and Resume Analysis Platform
June 1, 2026 – Present
Developed an AI-powered recruitment platform for resume parsing, ATS evaluation, candidate profiling, and job-description matching using LLMs and NLP techniques. Implemented Retrieval-Augmented Generation (RAG) pipelines using LangChain and FAISS to enable intelligent document retrieval and contextual candidate analysis. Designed FastAPI-based backend services for resume processing, semantic search, and automated interview question generation workflows. Built modular AI components for candidate recommendation, keyword extraction, and executive summary generation, reducing manual screening efforts and improving recruitment efficiency.
Atlas-Project Management and Workforce Automation Platform
June 1, 2026 – Present
Developed an enterprise project management platform for task tracking, team collaboration, and resource allocation across multiple projects and departments. Designed backend APIs and database workflows for project scheduling, role-based access control, and real-time project status management. Implemented workforce automation features, including shift chart management, attendance tracking, and reporting dashboards to streamline operational processes. Built scalable and maintainable backend services that improved workflow efficiency and reduced manual administrative effort through process automation.
AWS Certified Cloud Practitioner
Amazon Web Services (Coursera)
June 1, 2026 – Present
Microsoft Azure Fundamentals AZ-900
Microsoft
June 1, 2026 – Present
Prompt Engineering for Developers
Infosys Springboard
June 1, 2026 – Present
Data Analysis with Python
IBM
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic projects and professional experience align well with an AI Engineer role, showcasing a clear passion for AI and its practical applications. Their involvement in hackathons and community contributions indicates a proactive, innovative, and collaborative spirit. The diversity of projects (HR platform, project management, intelligent robot) demonstrates adaptability and a broad interest in applying AI to various domains, which is a good fit for dynamic environments. The candidate's current role as an 'AI Engineer Trainee' and their academic background in 'Artificial Intelligence and Data Science' directly match the target role.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through participation in hackathons and developing complex AI solutions. Their collaboration with cross-functional teams indicates good teamwork and communication. The ability to deliver production-ready AI solutions under time constraints (Lightning Coders Trophy) suggests a results-oriented and adaptable work attitude. The active contribution to the AWS Cloud Computing community highlights a proactive learning and sharing mindset.