Abhinav Anand

Building Instamart for Retailers (Tezz) and HoReCa (Assure) Stack - Go, Java, React, AWS

Continued working as an everything engineer. - Built a DLT viewer alternative for testers with advanced features like Root case analysis and Similar ticket recommendation. - Engineered a self service flow to send filtered DLT logs to elasticsearch. - Did multiple POCs such as, building a Dbeaver like interface to view & manipulate Delta tables, building a config driven dashboard to view teamwise/dept wise KPI metrics for management visibility etc.

Received PPO Worked as an everything engineer in this role, majorly building self service capabilities in our data platform.

- Worked on Automatic Ticket Service API in Golang. - Added endpoints in Log-service API. - Worked on an end-to-end API in Flask and deployed on Azure App service. - Tech Stack - Python, Golang, Postgres, PySpark, Databricks, Azure Data lake, Azure Data Factory, App service and other Azure services.

Responsibility - Application Developer (Frontend, Backend, DevOps) Client 1: Independently developed and deployed a full MVP for a UK-based renewable energy client—built a marketplace connecting solar installers with building prospects, featuring AI-based solar panel visualization, OpenStreetMap integration, and detailed filtering. Led end-to-end CI/CD (GitHub Actions) and AWS deployment; automated data scraping, insights generation, and Apollo.io integration for targeted outreach campaign. Client 2: Architected a web version of a US client's FOIA redaction desktop tool—integrated PSPDFKit, in-house AI for redaction suggestions, robust RBAC, and a subscription model. Delivered full-stack features across frontend, backend, and DevOps with a strong focus on performance, scalability, and user experience.

• Worked with the team on a Machine Learning model to predict wildfire by classifying the smoke detected by the sensor. • Deployed the model on AWS and later made the model compatible with the Bosch BME688 sensor using tinyML.

- Migrated API from flask to Django. - Implemented some additional features according to the requirements.

- Organized webinars and contests to promote competitive programming on the campus.

- Mentored around 100+ students in Competitive coding and Machine Learning domain. - Conducted sessions on GIT, How to start your CP journey and Basics of ML for my mentees. - Reviewed more than 200 PRs during the program.

- Helped 50+ students in starting their open source journey. - Took sessions on best coding and open source contribution practices.

Tried teaching myself CS fundamentals.