Hi I'm

Pavani Ayanambakam

I am graduated 🎓 from University at Buffalo, with MS in Computer Science and Engineering with a 3.87 GPA. I build innovative applications by combining full-stack development with AI-driven solutions.With experience as a Full Stack Developer, I have worked with technologies like Angular, Python, Node.js, and GoLang, along with ML frameworks such as TensorFlow and scikit-learn.

My interests include Software Development and Testing, ML, DL and Natural Language Processing.


My Resume
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About Me

My introduction

Over the course of my career, I've had the opportunity to work at Tata Consultancy Services (TCS) and nVipani Technology Solutions, where I gained hands-on experience in full-stack development using Angular, Python, Node.js, React, and GoLang. At TCS, I worked on the B24G project, building dashboards to monitor 5G network infrastructure. I was involved in both frontend (UI/UX) and backend development, creating interactive user experiences and handling data processing. Additionally, I utilized AWS services like S3 for storing and managing large volumes of network logs and reports, and DynamoDB for handling real-time data retrieval and monitoring metrics, ensuring smooth performance and scalability. At nVipani, I developed ShopConnect, a B2B e-commerce shopping platform, where I worked on building interactive UI components and backend services to streamline the shopping experience.

Beyond my professional experience, I’ve worked on several projects that blend software development with AI/ML. I built a Virtual Classroom platform, an AI-powered chat system, and a Hand Gesture Recognition system for real-time applications. Additionally, I developed ShapeViewer, a tool for visualizing and analyzing geometric structures, worked on Used Automobiles Price Prediction and Object Detection using Semantic Segmentation. I'm always excited about building scalable applications, integrating AI into real-world solutions, and tackling complex technical challenges. Right now, I am looking for opportunities where I can apply my skills in full-stack development and machine learning to make a real impact.

1 Strong Internship
Experience
10+ Imapctful
AI/ML and Core CSE Projects
4 years of experience in Full stack Development
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Qualifications

My Career Path
Experience
Education

MS in Computer Science and Engineering

State University of New York at Buffalo
Aug 2023 - Dec 2024
3.87/4.0 (AI/ML Track)

BTech in Computer Science and Engineering

8.89/10.0

Full Stack Developer

CBRE
April 2025 - Present
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  • Developed UI for Workorders module in Angular to manage activity and task requests from the CMM admin, integrating with backend services built using Java and Spring Boot.

  • Written and integrated Kafka producers and consumers to handle streaming data between microservices. Used Confluent Kafka platform for managing topics, schemas (Schema Registry), and stream governance.

  • Tracked release tags, log patterns, and error rates in Datadog to support rapid debugging and deployment validation.

Full Stack Developer

Tata Consultancy Services
July 2021 - August 2023
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Service Certificate

  • TCS Service certificate

  • Proficient in utilizing Angular, Python to design dynamic interfaces and built robust server-side logic. Designed more than 16 APIs to support various functionalities within the B24G project, adhering to RESTful principles.

  • Designed and implemented a dashboard to summarize, track, and monitor 5G core network infrastructure’s performance and stability. Achieved a 30% increase in test coverage and a 15% reduction in bug discovery time.

  • Developed more than 35 UI components (charts, graphs, tables, maps) to visualize network data, 15+ interactive elements for data filtering, drilling down, and custom views.

MEAN Stack Developer

nVipani Technology Solutions
March 2019 - June 2021
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nVipani Technology Solutions

  • Developed an e-commerce, B2B application called “ShopConnect,” an AR/VR-based integrated video shopping platform. Robust back-end infrastructure was built using Node.js that handled the complex logistics of 5,000+ product listings across 238 B2B suppliers.

  • Gained expertise in React, Bootstrap by building intuitive, aesthetic interfaces that boosted user engagement and sales by 24% compared to traditional B2B platforms. Designed and implemented RESTful APIs for product data retrieval, order processing, and secure video chat functionalities.

Skills

My technical level

Programming Languages

Utilized programming language skills across various projects
80%

Python

75%

JavaScript/TypeScript

90%

Java

90%

HTML/CSS

90%

SQL

65%

C/C++

Tools and Technologies

To build robust solutions
95%

Angular

80%

Git

60%

AWS

90%

Android Studio

95%

Visual Studio Code/Eclipse ID/IntelliJ

Frameworks

90%

Flask

90%

ML libraries(pandas,Scikit-learn)

80%

Oracle DB

75%

CSS Frameworks

70%

React

70%

NodeJs

Libraries

95%

PyTorch

80%

Pandas

90%

skLearn

90%

TensorFlow

95%

Keras

95%

OpenCV

People Skills

Collaboration and TeamWork

Leadership and Initiative

Strong Communicative Abilities

Client and Stakeholder Management

Contributions

My Projects

PROJECTS

Pluck And Pack

  1. Pluck And Pack

    2024

    Designed and developed a React-based grocery shopping platform, "Pluck and Pack," enabling seamless online shopping experiences.

    Implemented key features such as product browsing, cart management, real-time inventory updates, and an intuitive shopper-assignment system.

    1. Browse & Select: Users can explore a dynamic catalog of grocery items, filter products, and add them to their cart.
    2. Assign & Pack: The system assigns shoppers dynamically based on location and availability, optimizing the order fulfillment process.
    3. Track & Deliver: Customers can track order status in real-time, ensuring efficient and transparent grocery delivery.
Malware Threat Detection

  1. Q&A using RAG(GenAI)

    2024

    Implemented, and demonstrated a sophisticated question-answering system utilizing Retrieval-Augmented Generation (RAG) technology.

    The project aims to highlight the system's ability to perform real-time information retrieval from a diverse document set, fuse this information seamlessly, and produce answers that are not only accurate but also contextually enriched.

    1. Retrieve: Given a user input, relevant splits are retrieved from storage using a Retriever. Generate: A ChatModel / LLM produces an answer using a prompt that includes the question and the retrieved data.
Class Attendance through Face detection and recognition

  1. Class Attendance through Face detection and recognition

    2023

    Detects and recognizes students' faces using a camera feed (e.g., webcam or IP camera).

    Matches the detected faces with a database of pre-registered students.Automatically marks attendance based on successful face recognition

    Technologies Used are:

    1. Python: Core language for development.
    2. OpenCV: For face detection and recognition.
    3. GUI Library (Tkinter or PyQt): For building a desktop interface
Malware Threat Detection

  1. Malware Threat Detection using ML models

    2021

    Trained model with huge Malware Threat dataset with 83 features and evaluated it’s performance using confusion matrix.

    Used Machine Learning Models like Gradient Boosting, Sequential neural network, Light GBM to detect the patterns of the malware and achieved 86% accuracy

    1. Machine Learning models developed include: Sequential Neural Networks,Decision tree classifier, Random Forest Classifiers, XGBoost, LightGBM

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Email Me

pavaniayanambakam@gmail.com

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