ANUPRABHA R

Generative AI Engineer

https://www.opentalent.in/anuprabha-r

Generative AI Engineer with less than a year in Deep Learning, Prompt Engineering, and RAG architect

Key Strengths

Strong academic background in Computer Science and Engineering with a specialization in AI/ML.
Demonstrated project experience in LSTMs, GANs, RNNs, and autoencoders, directly relevant to Generative AI.
Familiarity with key Generative AI concepts like LLMs, RAG, Prompt Engineering, and Vector Databases.
Experience with Python, FastAPI, and API development, essential for building AI applications.
Exposure to data management (SQL, MongoDB, Firebase, NumPy, Pandas) and cloud basics (Docker, Cloud Computing Basics).

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's academic projects and hackathon participation demonstrate a proactive, hands-on approach to learning and problem-solving. The diversity of projects, from generative AI research to database management and real-time safety solutions, indicates adaptability and a broad interest in applying technical skills. The explicit mention of collaborative communication aligns with team-oriented environments. The target role of Generative AI Engineer aligns well with the candidate's stated specialization and project focus.

Soft Skills & Operational Fit

The candidate highlights problem-solving, research-driven development, and collaborative communication as soft skills. Project descriptions suggest an ability to work in fast-paced environments (Uyir Hackathon) and manage data integrity. The focus on optimizing algorithmic efficiency and monitoring system performance indicates an operational mindset relevant to deploying AI models.

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About

Enthusiastic and innovative Computer Science Engineering graduate with a strong specialization in Artificial Intelligence and Machine Learning. Passionate about Generative AI, with deep academic and project-based experience in LSTMs, GANs, RNNs, and autoencoders. Proficient in Python, database architectures (including vector database concepts), and API integration. Eager to leverage foundational expertise in Prompt Engineering, RAG architectures, and LangChain to build cutting-edge Generative AI solutions as a Generative AI Engineer at Polluxa.

Top Skills

Vector DatabasesPrompt EngineeringMongoDB

Education

Hindusthan College of Engineering and Technology

Bachelor of Engineering · Computer Science and Engineering

August 1, 2022 – June 30, 2026

Hindusthan Matriculation Higher Secondary School

Class XII · TamilNadu State Board

June 1, 2021 – May 31, 2022

Hindusthan Matriculation Higher Secondary School

Class X · TamilNadu State Board

June 1, 2019 – May 31, 2020

Projects

Generative AI Research & Implementation

June 25, 2026 – Present

Core Focus: Advanced Deep Learning Architectures. Hands-on experience in building and tuning LSTMs, GANs, and autoencoders for sophisticated predictive and generative tasks. Researched image-based animal classification systems, focusing on optimizing high-dimensional data handling and neural network feature extraction.

Fraud Detection System

June 25, 2026 – Present

Managed large-scale datasets hosted in cloud-based environments to evaluate system behavior and maintain high data integrity, foundational for RAG-based architectures. Monitored complex data flows, ensuring clean, high-quality data ingestion—a critical requirement for building reliable Generative AI pipelines.

Crime Prediction and Analysis

June 25, 2026 – Present

Analyzed system performance by monitoring compute and memory utilization during heavy, data-intensive machine learning analysis routines. Optimized algorithmic efficiency, ensuring robust backend stability—a vital practice when deploying Generative AI models at scale.

Smart India Hackathon: Alumni Database Management system

June 25, 2026 – Present

Developed an Alumni Database Management system, mastering the structured ingestion and relational mapping required for efficient data handling.

MSME 4.0 Hackathon: Railway Management System

June 25, 2026 – Present

Engineered a Railway Management System with backend scheduling and logic workflows.

Uyir Hackathon 2024 (Finalist): Real-time safety solutions

June 25, 2026 – Present

Coordinated within a fast-paced development sprint to build real-time safety solutions, emphasizing rapid prototyping and feature validation.

Key Strengths

Strong academic background in Computer Science and Engineering with a specialization in AI/ML.
Demonstrated project experience in LSTMs, GANs, RNNs, and autoencoders, directly relevant to Generative AI.
Familiarity with key Generative AI concepts like LLMs, RAG, Prompt Engineering, and Vector Databases.
Experience with Python, FastAPI, and API development, essential for building AI applications.
Exposure to data management (SQL, MongoDB, Firebase, NumPy, Pandas) and cloud basics (Docker, Cloud Computing Basics).

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit