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AI Engineer with 2+ years in Prompt Engineering & Web Development
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Assessing your cultural and operational fit
Recent Computer Science graduate with practical experience building AI systems, web applications, and IoT solutions. Passionate about solving real-world problems using modern technology, quick to learn, and ready to contribute from day one in a product-focused team.
Andhra University College of Engineering
B.Tech · Computer Science and Engineering
N/A – June 30, 2025
Vallen Softtech
Web Development Intern
July 1, 2024 – Present
India
I&T-LAB
Full-Stack Development Intern, Team Lead
October 1, 2023 – Present
India
Technohacks
Cybersecurity Intern
October 1, 2023 – Present
India
Hybrid-Based Guava Disease Detection
June 28, 2026 – Present
Designed a hybrid AI pipeline combining YOLOv8 for object detection and DenseNet for disease classification, achieving high accuracy on agricultural leaf images. Integrated the inference pipeline into a web-based interface enabling users to upload images and receive real-time disease diagnosis and recommendations.
IoT-Based Health Monitoring System
June 28, 2026 – Present
Developed an end-to-end IoT healthcare monitoring platform integrating Arduino UNO, LoRa communication, Azure IoT Hub, GPS tracking, and physiological sensors for real-time remote monitoring. Integrated SX-1278 LoRa module for long-range wireless transmission and connected the system to Azure IoT Hub for cloud-based monitoring and data storage.
CyberRAG - Multi-Agent RAG Platform
June 28, 2026 – Present
Architected a 5-agent pipeline covering ingestion, chunking, embedding, retrieval, and generation that processes live cybersecurity intelligence feeds in real-time using Kafka KRaft for event streaming and Qdrant for vector storage. Built a 120-item adversarial benchmark dataset to evaluate prompt injection resilience across the multi-agent pipeline, establishing a reusable evaluation harness for response quality. Shipped a full-stack Next.js interface with streaming responses, production-ready on Google Colab T4 via ngrok, publicly documented and MIT-licensed on GitHub.
View ProjectGNSS Satellite Orbit Error Prediction
June 28, 2026 – Present
Developed RNN models to learn temporal satellite orbit deviations from SP3 ephemeris data. Designed preprocessing pipelines for multi-satellite coordinate extraction and time-series forecasting. Improved prediction of orbital error trends for navigation accuracy.
Introduction to Programming Using Python
Microsoft Certified
June 1, 2026 – Present
Azure AI Fundamentals
Microsoft Certified
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's involvement in hackathons, coding competitions, and leadership roles in team projects indicates a proactive, collaborative, and growth-oriented mindset. The diversity of academic projects (RAG, Computer Vision, IoT, GNSS) shows a broad interest in various technical domains, which can be beneficial for cross-functional collaboration. The target role of AI Engineer aligns well with the candidate's project experience in building AI systems and pipelines.
Soft Skills & Operational Fit
The candidate demonstrates strong problem-solving skills through hackathon participation and project work. Leadership experience as a team lead suggests good collaboration and communication within a team setting. The ability to document threat vectors and mitigation notes indicates attention to detail and structured reporting. The candidate's passion for solving real-world problems aligns well with a product-focused team environment.