Hi, I'm Prakruthi Koteshwar

I’m a software developer with 3+ years of experience building web applications and backend systems. My work has involved full-stack development, cloud platforms like AWS, and integrating AI-based tools into applications. I enjoy building practical solutions, improving system performance, and working on problems that require both engineering and creative thinking.

View My Work

Projects

AI & Machine Learning

Traceability Engine: AI-Powered VCS Automation

CLI tool that prevents documentation drift by synchronizing source code and method documentation using AST parsing and Llama-3.3-70B. Processes 100+ functions in parallel using concurrent execution, reducing manual documentation effort by ~70%.

Large Language Models (LLMs) Llama 3.3 AST Parsing Concurrency ThreadPoolExecutor CLI Development VCS Automation

MNIST Digit Classifier — CNN vs MLP

Built a deep learning system to recognize handwritten digits (0 - 9) from uploaded images. Implemented and compared MLP and CNN architectures, demonstrating CNN’s superior performance for image data. The system includes image preprocessing with OpenCV and a FastAPI-based REST API for real-time predictions.

Deep Learning CNN MLP OpenCV FastAPI Image Classification Neural Networks

FinTune-Sentinel: LoRA-Enhanced Auditor

A specialized financial LLM fine-tuned using LoRA (Low-Rank Adaptation) to map 10-K risk factors with high precision. By freezing the base model and training rank-decomposition matrices, I achieved state-of-the-art FinQA accuracy while reducing trainable parameters by over 90%.

LoRA / PEFT Llama 3.2 Rank Decomposition Quantized Fine-Tuning SEC-Compliance

Agentic Corrective RAG (CRAG)

In Progress

RAG LLMs Agentic Systems AI Research

SupplyChain-Sense: Multi-Tier Risk Mapping

In Progress

Graph RAG LLMs Agentic Systems AI Research

Full Stack Development

WeCureIT

Designed and developed a web-based system for a multi-location medical clinic that enables patients to book appointments with doctors based on specialty and facility availability. The platform supports dynamic doctor scheduling, facility capacity management, secure patient/doctor accounts with 2FA, and an admin dashboard for managing clinics, doctors, and website content.

Spring Boot Next.js Firebase Tailwind CSS Role-Based Access Control

High-Performance Distributed Job Scheduler (Go + gRPC)

Built a distributed task scheduler in Go with a gRPC-based communication layer between a centralized Master node and multiple Worker nodes. Implemented a priority-aware scheduling engine using a bin-packing strategy to efficiently allocate resources across the cluster and maximize utilization. Added constraint-based scheduling (Node Affinity) to intelligently match tasks with appropriate hardware profiles. The system is designed for scalability and resilience, with ongoing enhancements including fault recovery, resource quotas, and real-time cluster telemetry.

Go gRPC Distributed Systems Task Scheduling Bin Packing Concurrency

Blog Platform

Developed full-stack blogging platform with markdown editor, user authentication, and SEO optimization. Implements lazy loading for performance.

Next.js Firebase Tailwind

Logic & Programming

Tower of Hanoi Solver

Implemented recursive algorithm to solve Tower of Hanoi puzzle. Visualizes move sequences and calculates optimal solution count (2^n - 1).

Python Recursion Visualization Javascript HTML/CSS

Dijkstra's Shortest Path

Created interactive simulation of Dijkstra's algorithm for finding shortest paths in weighted graphs. Includes step-by-step visualization and performance metrics.

Python Graphs Algorithms

Password Organizer using Tree

Passwords are stored and organized using a tree structure that enables efficient searching, insertion, and categorization of credentials by platform or service.

Tree Data Structure Hierarchical Storage Search Optimization Data Organization Secure Storage

Experience

Software Engineer Consultant

DOT Consulting LLC
Feb 2026 - Present
  • Evaluated and implemented cloud-based High Performance Computing (HPC) infrastructure on AWS, focusing on scalable and cost-efficient workload execution.
  • Configured Linux-based environments, shared storage systems, and the Slurm job scheduler for distributed HPC workloads.
  • Provisioned AWS Spot Instances with autoscaling and monitoring using CloudWatch and AWS Budgets to optimize compute costs and resource utilization.
Tech Stack: AWS (EC2, Spot Instances, CloudWatch, Budgets), Linux, Slurm, HPC, Python, Perl, Bash, Workflow Automation

Graduate Research Assistant - George Washington University

George Washington University
Jan 2026 - Present
  • Developed full-stack research tools using Node.js and React (Remix) to support web security and privacy data analysis.
  • Integrated Google Gemini AI APIs to automate data processing, content analysis, and intelligent query workflows.
  • Implemented Elasticsearch indexing and search pipelines to enable fast retrieval and analysis of large research datasets.
  • Built web scraping pipelines to collect and structure web data for security and privacy research experiments.
Tech Stack: Node.js, React (Remix), Google Gemini AI Integration, Elasticsearch, Web Scraping, RESTful APIs, JavaScript/TypeScript, MongoDB, Git, CI/CD

Software Intern

PACCAR Financial
May 2025 - Aug 2025
  • Developed UiPath-based RPA workflows to automate data processing tasks in finance applications, reducing manual effort and improving operational efficiency.
Tech Stack: UiPath, RPA, ASP.NET (.NET), Salesforce, Workflow Automation, Excel Automation, API Integration

Software Developement Engineer in Test - II

HashedIn by Deloitte
Aug 2021 - Jun 2024
  • Developed GenAI-powered testing tools with Node.js backend services and modern frontend interfaces to automate test case generation and workflow analysis.
  • Integrated LLM-based capabilities into enterprise testing frameworks to support intelligent test generation and validation across applications.
  • Built and enhanced automation utilities for Java-based applications, enabling scalable testing and AI-assisted debugging workflows.
  • Designed full-stack solutions combining frontend interfaces, Node.js services, and AI models to improve testing efficiency and developer productivity.
Tech Stack: Node.js, Java, JavaScript/TypeScript, GenAI, LLMs, REST APIs, Test Automation, Full-Stack Development

Resume

Education

Master of Science in Computer Science

George Washington University

Graduation: 2026

GPA: 3.8/4.0

Skills

Languages:

Python JavaScript Java SQL

Tools & Frameworks:

TensorFlow React Django PostgreSQL

Certifications

Google Cloud Professional

Issued: March 2024

AWS Cloud Foundation

Issued: Aug 2024