const developer = {
name: "Phalguna Avalagunta",
role: "Cloud & AI Developer",
location: "London, UK",
education: "MSc Computer Science @ University of East London",
availability: "Immediate",
passion: "Building scalable solutions that matter"
};Innovative Cloud & AI Developer with hands-on experience building production-ready applications using AWS, Python, and Machine Learning. Currently completing MSc Computer Science at University of East London with immediate availability for full-time roles.
- Immediate Impact: Ready to contribute from day one with practical experience in AWS Lambda, EC2, S3, and SageMaker
- Modern Tech Stack: Proficient in Python, JavaScript, React, Node.js, Docker, Kubernetes, and TensorFlow
- Problem-Solving DNA: 2+ years analyzing complex datasets and optimizing processes - reduced processing time by 30%
- Continuous Learner: Pursuing AWS Solutions Architect certification while building real-world projects
Deployed full-stack application using EC2, RDS, S3 with auto-scaling and load balancing. Handles 1000+ concurrent users with 99.9% uptime.
- Tech: React, Node.js, PostgreSQL, Docker, AWS
- Highlights: Integrated Stripe API, implemented CI/CD pipeline
Built ML model using LSTM achieving 85% accuracy. Deployed on AWS SageMaker with REST API for real-time predictions.
- Tech: Python, TensorFlow, Flask, SageMaker
- Highlights: Processes 10,000+ predictions daily
Serverless architecture using Lambda, API Gateway, DynamoDB with WebSocket implementation for real-time updates.
- Tech: Python, JavaScript, AWS Lambda, Chart.js
- Highlights: Processes 1M+ events daily with sub-second latency
Computer vision application using CNN for object detection with 92% accuracy on custom dataset.
- Tech: Python, OpenCV, PyTorch, Docker
- Highlights: Deployed as containerized microservice on AWS ECS
Intelligent chatbot using BERT for intent classification, handling 50+ intents with context awareness.
- Tech: Python, BERT, Flask, Lambda
- Highlights: Integrated with Slack, deployed serverless
Automated deployment pipeline using Jenkins, Docker, and AWS CodePipeline.
- Tech: Jenkins, Docker, Terraform, Git
- Highlights: Reduced deployment time by 70%
Data Analyst @ Morae (Jul 2022 - Sep 2024)
- Analyzed complex datasets using Python and SQL
- Automated processes reducing manual work by 30%
- Built dashboards and visualization tools
- Managed databases with 10,000+ records
Operations Analyst @ Sagility (Jul 2021 - Jul 2022)
- Processed high-volume data with 99% accuracy
- Developed process improvements increasing efficiency by 25%
- Worked with APIs and data integration tools
MSc Computer Science - University of East London (Sep 2024 - Jan 2026)
- Key Modules: AWS Cloud Computing, Artificial Intelligence, Machine Learning, Big Data Analytics
BSc Computer Science - Sri Venkateswara University (2018 - 2021)
- π― AWS Certified Solutions Architect - Associate (In Progress - Expected Jan 2025)
- π― AWS Certified Developer - Associate (Planned - Feb 2025)
- π― Google Cloud Digital Leader (In Progress)
β Deployed serverless e-commerce platform handling 1000+ concurrent users on AWS β Built ML model for predictive analytics achieving 85% accuracy β Developed RESTful APIs and microservices with 99.9% uptime β Reduced processing time by 30% through automation
- π§ Email: [email protected]
- π§ Personal: [email protected]
- π± Phone: +44 07741820922
- πΌ LinkedIn: phalguna-avalagunta
- π Location: London, UK
βοΈ From Phalguna Avalagunta

