— Experienced in Backend, Cloud & Distributed Systems

I have a strong background in software development and engineering, with significant experience in building scalable applications and optimizing infrastructure. My recent role as a Software Engineer Co-op involved enhancing AWS-based systems with serverless technologies, developing high-performance tools, and automating CI/CD pipelines. Previously, as a Full Stack Developer, I designed and implemented RESTful APIs, improved user interfaces with modern frameworks, and optimized deployment processes using Docker and Kubernetes. My early career experience includes developing APIs and real-time data processing pipelines, as well as improving database performance and system monitoring. Throughout my career, I have demonstrated expertise in various technologies and methodologies to drive efficiency and innovation

— Technical Skills

-Languages: Python, Java, C++, Dart, JavaScript, Typescript, SQL
-Frameworks: Node.js, Spring Boot, Flutter, Django, Flask, ReactJS, Vue.js, NextJS, Angular
-Cloud Infra AWS, GCP, Kubernetes, Terraform, Docker, Ansible, Linux, Git, Jenkins
-Protocols SMTP, UDP, gRPC, HTTP, TLS, TCP/IP, DNS, DHCP
-ML/Big Data Kafka, RabbitMQ, Redis, Amazon S3, SQS, Apache Spark, Hadoop, Elasticsearch

— Work experience

Software Engineer Co-op

Prime Medicine / July 2023 - Dec 2023

•Achieved 80% load distribution deploying serverless AWS ECS Infrastructure as code pipeline configuring load balancer (ALB), ECR, Docker, VPC, subnets, CloudWatch using AWS CDK Stack 

• Developed a File Parser Tool in production using AWS Lambda functions triggered by messages from SQS queues storing pegRNA data in S3 buckets with CloudWatch logs resulting in a 75% faster data ingestion rate

 • Built a FastAPI app with RESTful APIRouter for NGS team improving 50% response time interacting with Benchling SDK (postgres), Swagger docs, Docker, JWT tokens and OAuth 

• Developed Javascript-SQL based app populating pegRNA well platemap using Benchling APIs reducing 20% annual cost 

• Automated CI/CD GitHub Actions pipeline resolving more than 50 production bugs/tickets during JIRA daily scrums 

• Increased code coverage from 10% to 75% incorporting unittests, mocktests, pylint, pydantic, and integration test

Full Stack Developer

Tech Mahindra / Aug 2019 - Dec 2021

• Developed migration framework using Java, J2EE, Core Spring 3.0, Hibernate 3.0, Web Services, SOAP API

• Implemented Kafka Topic payment events leveraging Spring Boot's SAGA Pattern with Hibernate ORM, improving 40% transaction resilience

• Orchestrated Kubernetes, Elasticsearch, Zipkin distributed tracing resulting 15% improved scalability & indexing

• Implemented Spring Security Authorization, GraphQL APIs payment retrieval reducing 75% network overhead

• Build robust CI/CD pipeline on Jenkins and utilized JUnit, Mockito Framework for Unit & Integration testing

Software Developer

BSNL / Dec 2018 - May 2019

• Developed RESTful APIs for telecom system internal applications, improving integration & data retrieval times by 40% 

• Assisted in developing real-time data processing pipelines using Apache Kafka, contributing to a 30% improvement in system responsiveness for live telecom data streams by reducing latency 

• Optimized SQL, PL/SQL, and T-SQL database queries using PostgreSQL, improving 30% in query performance

 • Configured logging and monitoring solutions using ELK Stack (Elasticsearch, Logstash, Kibana) and Prometheus, improving system observability and reducing incident response times by 40% 

• Established robust CI/CD pipelines using Jenkins, automating build, test, and decreased deployment time by 60%

— Education

Northeastern University

Master's degree, Information Systems / 2022 - 2024
 

University of Mumbai

Bachelor's degree, Electronics & Telecommunications / 2015 - 2019
 

— Projects

Google Hackathon

Developed a revolutionary mental health AI social app using Flutter, Dart, dio networking, bloc state, seamlessly integrating Google and Apple Pay for convenient contributions / Feb 2024

Demo: https://devpost.com/software/caresync-8vxn3l

Github: https://github.com/NihalGajbhiye/GoogleHackathon

Distributed Chat Server

Employs Socket.io for real-time communication, Redis manages cache/pub-sub, MongoDB ensures persistence, HAProxy handles load balancing, and React boosts frontend interactivity for a scalable chat app / Jan 2024

Demo: https://vimeo.com/921546917?share=copy

Github: https://github.com/NihalGajbhiye/ConnectHub-Distributed-Chat-Server

AWS/GCP Infrastructure

Implemented Pulumi Python script automating AWS and GCP infrastructure deployment, managing VPC, RDS, EC2 auto-scaling, and integrating with SES and Route 53 for email notifications and DNS routing / Nov 2023

Github: https://github.com/NihalGajbhiye/Infrastructure-As-Code-AWS-GCP-Pulumi

LifeLine Enterprise Application

LifeLine is a user-friendly application dedicated to community welfare and facilitates seamless connections between volunteers, help seekers, donors, and professionals. Managed by the Lifeline Manager, our platform coordinates requests for assistance, transportation, medical aid, and data transmission to doctors. With the mayor's oversight and the support of supervisors and administrators, we ensure efficient operations to serve those in need. / Jan 2023

Github: https://github.com/NihalGajbhiye/LifeLine-Enterprise-Application
 

X-Ray-Image-Processing-Pneumonia-Prediction-Model

The deep learning model is built using the Keras Sequential API with the following architecture:

• Convolutional layers (Conv2D)
• Batch normalization layers (BatchNormalization)
• Max-pooling layers (MaxPool2D)
• Dropout layers (Dropout)
• Flatten layer
• Dense layers (Dense)

Github: https://github.com/NihalGajbhiye/X-Ray-Image-Processing-Pneumonia-Prediction-Model
 

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