Hi, my name is

Siddharth.

I write software.

Enthusiastic Computer Science student with a strong foundation in software development and a passion for building innovative solutions. Eager to leverage my skills and collaborate on impactful projects as a software engineering intern."

Resume

About Me

I am a graduate student at San Jose State University, specializing in Software Engineering with a focus on enterprise software solutions. With experience in full-stack development, machine learning, and performance monitoring, I am passionate about designing scalable and impactful software. I look forward to applying my skills in collaborative, innovative environments through software engineering internships.

I am currently working on an Event Storage System project | visit github. Which can be self hosted and with Serverless Cloud Compute, developers can benefit fast log-monitoring.

Here are a few technologies I've been working with recently:
  • Golang
  • Python
  • Apache Kafka
  • AWS Lambda
  • Kubernetes
  • AI & RAG

Experience

Software Engineer - LogicMonitor SDE II
Dec 2022 - Aug 2024
View the project

Developed high-availability backend solutions for large-scale cloud and log monitoring, ensuring performance and cost efficiency.

  • Built backend microservices in Java and Golang to process over 10TB of data daily across 5,000+ devices, maintaining high availability.
  • Improved data retrieval efficiency by 19% with Redis-Cache and AWS Lambda, reducing latency for real-time monitoring.
  • Created an OKTA log collector with AWS CloudFormation, saving $20,000 annually by replacing third-party solutions, and developed APIs to enhance observability across IaaS, PaaS, and SaaS environments.
Associate Software Engineer - LogicMonitor SDE I
Sep 2020 - Dec 2022
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Collaborated on developing advanced monitoring solutions and tools to improve infrastructure performance and observability for clients.

  • Contributed to a Java-based monitoring agent for 10,000+ infrastructure components, reducing errors by 25% and increasing log ingestion speed by 30% using serverless computing on AWS, GCP, and Azure.
  • Led the development of the “Logsource” feature and Python/Java SDKs, boosting infrastructure observability by 40% for over 100 clients and enhancing customer satisfaction by 15%.
  • Optimized Kubernetes monitoring with Helm, reducing deployment time by 20% across 100+ client clusters, and created open-source Ruby plugins for Fluentd and Logstash with over 100K downloads for improved data ingestion.
Web Development Intern - AutoIntell Services
Feb 2018 - July 2018

Built a resourceful IoT website from the ground up with a team, supporting amateur developers within the company.

  • Designed and developed the site architecture, integrating a Python backend with AWS DynamoDB for efficient NoSQL storage.
  • Implemented a video upload feature using boto3 and AWS S3, enabling smooth object storage for user-generated content.

Education

Aug 2024 - May 2026
Masters in Software Engineering
San Jose State University
GPA: 3.8 out of 4.0

Courses I have taken

  • Enterprise Distributed Systems, Enterprise Application Development, Enterprise Software Platform, Data Mining
  • Machine learning, Artificial Intelligence and Data Engineering, Web UI Technologies, Cyber Security
Aug 2016 - May 2020
Bachelors in Computer Engineering
Pune University
GPA: 9.1 out of 10

I majored in Computer Engineering with minor in Data Science.

  • Data structues and Algorithms, Operating Systems, Databses, Engineering Informatics were my favorite courses.
  • Practitioner’s Approach to Data Analytics, Predictive Analytics, Applied Machine Learning

Extracurricular Activities

  • Coding Club, Math Club
  • Movie Club, Pune Drama Club

Projects

Distributed Event Storage and Retreival System
Golang Microservives Apache kafka Docker Kubernetes S3 Serverless React
Distributed Event Storage and Retreival System
A micro-service based project which uses serverless compute to retrieve and search data from object storage like S3.
Visionary Recommender
Python OPEN AI Google AI Flask RabbitMQ
Visionary Recommender
This project is an AI-powered Visionary Recommender System that utilizes Retrieval-Augmented Generation (RAG) to analyze user-uploaded images, identify products (brand, model, defects), and deliver personalized recommendations.
Content Based Image Retreival
Python Tensorflow VGG16 CNN
Content Based Image Retreival
Convolutional Neural Network classifier with 93% accuracy using the Caltech-256 dataset. - Built a Flask-based web application that allows users to input images and receive relevant results, including similar images and associated weblinks, improving user interaction and search accuracy.

Achievements

LogicMonitor Star Performer
I was recognized by Rajesh Kulkarni (VP, LogicMonitor India) for my performance in 2023.

Get in Touch

My inbox is always open. Whether you have a question or just want to say hi, I’ll try my best to get back to you!
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