AI Engineer with less than a year in NLP, LLMs & RAG architectures
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Enthusiastic AI & ML Engineer with hands-on experience in NLP, LLMs, RAG architectures, and deep learning frameworks like TensorFlow and PyTorch. Proficient in Python, SQL, Docker, and CI/CD workflows, aiming to build scalable and intelligent AI systems in a dynamic organization.
Jawaharlal Nehru Technological University Anantapur
B. Tech · CSE (Artificial Intelligence)
N/A – June 30, 2026
Intelligent Question Answering System using LLM & RAG
June 24, 2026 – Present
Built an AI-powered question answering system using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). Implemented document embedding and vector similarity search for contextual information retrieval. Designed a pipeline to preprocess, chunk, and index large datasets for efficient semantic search. Integrated LLM APIs to generate context-aware responses with improved factual accuracy. Used SQL databases for structured storage and retrieval optimization. Developed REST APIs for real-time inference and integrated frontend interface. Deployed the application using Docker with CI/CD automation for scalable production deployment. Improved response relevance by implementing cosine similarity and embedding-based ranking.
Software Engineering Course
NPTEL
June 1, 2026 – Present
Google Cloud Computing Foundations & Generative AI
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's academic project demonstrates a focused interest in AI/ML, particularly in LLMs and RAG, which aligns well with an AI Engineer role. The listed certifications in Software Engineering and Generative AI further support this alignment and a proactive learning attitude. However, the lack of diverse project experience beyond a single academic project and no professional work experience limits the assessment of broader cultural fit, adaptability to different team structures, or exposure to varied business problems.
Soft Skills & Operational Fit
The candidate's project description indicates an ability to work through a complete development lifecycle, from design to deployment, suggesting good problem-solving and execution skills. The objective statement highlights enthusiasm and a desire to build scalable systems, which aligns with a dynamic organizational environment. However, without specific behavioral assessment data or team project details, it's difficult to fully assess soft skills like teamwork, leadership, or adaptability.