Software Engineer Spring Boot

Manaswi Ketha

***************@*****.*** linkedin.com/in/manaswiketha/ 860-***-**** Hartford, CT

SUMMARY

Software Engineer with ~2 years of experience developing scalable, customer-focused microservices using Java 11 and Spring Boot. Strong background in building cloud-native applications, deploying CI/CD pipelines, and ensuring system reliability using observability tools. Proficient in Agile methodologies and DevOps practices, with exposure to AWS and containerized environments. Passionate about clean code, performance optimization, and solving impactful problems for users at scale.

EDUCATION

Master of Science, Computer Science Bridgeport, Connecticut

University of Bridgeport May 2023 – December 2024

Course Work: Operating Systems, Object Oriented Programming, Web Development, Databases, Python, Deep Learning, Analysis of Algorithms

Bachelor of Technology, Computer Science & Engineering Andhra Pradesh, India

Vignan’s Foundation for Science, Technology and Research July 2017 – April 2021

TECHNICAL SKILLS

Core: Java, Groovy, Python, SQL,React

Framework & Tools: Spring Boot, RESTful APIs, Microservices

Databases: MySQL, PostgreSQL

Cloud & DevOps: AWS (Certified Cloud Practitioner), Concourse CI/CD, Git, GitHub, Jenkins (familiar)

Tools: Git, GitHub, Dynatrace, Humio, App Metrics

PROFESSIONAL EXPERIENCE

LTI MINDTREE Hyderabad, India

Software Engineer August 2021 – February 2023

· Developed and maintained microservices for enterprise applications using Java 11, Spring Boot, and RESTful APIs, enhancing scalability and modularity.

· Designed backend components with a focus on latency, resiliency, and high availability, aligning with cloud-native patterns.

· Built and optimized CI/CD pipelines using Concourse, leading to a 25% improvement in deployment reliability.

· Integrated monitoring tools (Dynatrace, Humio) to ensure production readiness and support quick resolution of incidents.

· Participated in all Agile ceremonies (sprint planning, retrospectives, daily standups), contributing to a 15% improvement in sprint velocity.

· Mentored interns and junior engineers, fostering a culture of code quality and continuous improvement.

· Gained hands-on experience with DevOps practices, containerized deployments, and proactive system monitoring.

· Worked with SQL databases like MySQL, aligning with data-intensive backend operations.

Software Engineer Intern June 2021 – August 2021

· Full-stack Java training with emphasis on web app development using Spring Boot and REST APIs.

PROJECTS

Project Name: Parkinsons Disease Detection Using Deep Learning August 2024 – December2024

· Model is trained using the Adam optimizer with a learning rate of 0.00001 and binary cross-entropy loss. The data is split into training and validation sets, with 80% used for training and 20% for validation.

· Developed a Resnet 50 model which achieved notable performance metrics with an accuracy of 82.5%.

Project Name: Plant Disease Detection using Deep Learning December 2020 – May 2021

· Plant disease detection can be done by observing the spot on the leaves of the affected plant. The method we are adopting to detect plant diseases is image processing using different deep learning models.

· Proposed ensemble technique has achieved high accuracy of 97.2 % when compared with pre-trained models.

CERTIFICATIONS

· AWS Certified Cloud Practitioner February 2025

ACHIEVEMENT

· Spot on Hats off Award, LTI Mindtree November 2022

Recognized for exceptional contributors to project success, demonstrating strong problem-solving and leadership skills.

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