Hey fellow devs! Glad you're here. I'm Abhinav Sivanandhan, a software engineer passionate about solving complex challenges with innovative solutions. 🚀

• 🎓 Studying M.S. Computer Science at New York University (Class of '25).
• 🧑‍💻 Former Software Engineer at Stryker, where I developed enterprise applications, automated workflows, and led DevOps initiatives.
• 💻 B.Tech in Computer Science & Engineering from VIT (Class of '21).

• 🛠️ Constantly tackling real-world problems through scalable design.
• 🌍 Building cloud-based distributed systems leveraging AI and modern web architectures.

(Node.js, React, Next.js, TailwindCSS, Redis, RabbitMQ, PostgreSQL, S3, GCP, AWS EC2, Stripe, LangChain.js, Datastax, OpenAI, Winston, Node-cron, Nodemailer)

Developed and deployed a scalable, event-driven e-commerce platform with a microservices-based architecture, leveraging asynchronous processing and Redis caching for high performance. Implemented secure, stateless authentication and role-based access control(RBAC) using JWT and bcryptjs, along with custom rate limiting middleware, and S3 bucket-based static asset management via pre-signed URLs with upload quotas. Designed automated background workers using Node-cron for scheduled tasks and message queue consumers for order processing using RabbitMQ. Enabled transactional email notifications with Nodemailer. Enhanced product retrieval with an LLM-powered RAG chatbot built using Next.js, LangChain.js, Datastax, and OpenAI. Ensured scalability and observability with Winston logging and deployed to AWS EC2.

(Terraform, AWS Lambda, Python, Streamlit, Perplexity Sonar API, CloudWatch, IAM, S3, VPC)

Built a zero-config AI-powered DevOps dashboard to optimize AWS infrastructure costs, security, and governance for small businesses and indie developers. Integrated cost monitoring, unused resource detection, and AI-generated Terraform refactoring. Parsed CloudWatch logs to recommend optimizations using Perplexity Sonar API. Automated security checks across IAM, S3, and VPC. Enabled live infra-to-code conversion and AI-driven risk summaries. Deployed using a custom Terraform pipeline with a Streamlit frontend. As it is portable, it's currently deployed to the same environment as the Digital Marketplace project.

(React, AWS Kinesis, DynamoDB, Amplify, Cognito)

Developed a scalable, GraphQL-based microservices platform for artists with real-time collaboration features and a personalized recommendation engine. Integrated AWS services to ensure high performance and scalability.

(Dask, Spark, DuckDB, PyArrow, Parquet)

Designed and implemented a distributed big-data ETL pipeline to process and analyze 500GB+ of highly nested JSON data related to adverse drug events. Leveraged Dask and PyArrow to efficiently flatten and convert the data into a distributed Parquet-based relational format, enabling fast querying and scalable exploratory analysis. Utilized Spark for parallel processing and optimized big data workflows.

(ResNet50, MobileNetV2, Flask, Kubernetes)

Built and deployed an image classification application using deep learning models. Utilized Kubernetes for container orchestration and dynamic scaling, achieving 99.68% availability and high performance with 28.54 transactions/sec.

(Next.js, Django, PostgreSQL)

Created a RESTful recipe recommendation system that leverages both content-based and collaborative filtering to deliver personalized suggestions. Built with a Next.js frontend and a Django backend.

I enjoy contributing to the open-source ecosystem, especially on projects that impact developers, researchers, and students. Some highlights include:

• PrairieLearn – Enhanced the online test-taking platform (widely adopted by multiple top universities including NYU) with intuitive frontend features and UI improvements using Python, TypeScript, and Mustache.

• ModelEarth Cloud – Built a Flask-based Jupyter execution service on Google Cloud Run with a RESTful API, GitHub webhook triggers, secure token handling, and fully automated CI/CD pipelines.

• ModelEarth Team – Developed and extended a Rust-based API deployed on Google Cloud Run (GCR) with GitHub OIDC authentication. Designed and implemented CI/CD pipelines using Cloud Build + Artifact Registry, integrated Azure Postgres and external AI services via REST endpoints, and set up robust secret management.

(MERN Stack, Google Calendar)

Developed an interactive event planning and scheduling app with a RESTful API suite. Integrated Google Calendar to streamline event organization and scheduling workflows.

• 👯‍♂️ If you're into AI, Web Development, or Infrastructure Engineering, I'm your guy!
• 🤝 Open to discussions, new ideas, and hacking on fun side projects together.

• 🌐 Portfolio: My Portfolio
• 💼 LinkedIn: linkedin.com/in/abhinav-sivanandhan
• 🖥️ GitHub: github.com/AbhinavSivanandhan :)