May 2024 – May 2025 · 1 yr · Reseach Triangle Park · Hybrid

• ● Founding engineer intern, developed applications that educate users on the importance of clinical trials and encourage trial enrollment.
• ● Designed, automated, and maintained GCP infrastructure using Terraform modules and Ansible playbooks, provisioning 100+ resources including VPCs, load balancers, and Compute Engines, while enforcing network security through firewall rules and IP whitelisting.
• ● Created volumes, secrets, and buckets required by the application in Google Cloud and integrated them into the GitHub Actions workflow, improving resource management.
• ● Dockerized 10+ applications, implemented multi-stage builds to reduce the build time by 53.3% (from 120 to 56 secs) and decreased the image size by 86% (from 590MB to 78MB).
• ● Established and optimized CI/CD pipelines from scratch using Python, Bash, and Nushell, introducing conditional base image builds, parallel execution, and reusable workflows in GitHub Actions to cut build times by 65.7% (from 350s to 108s).
• ● Deployed 10+ applications, including LLM frameworks and GenAI apps, to Google Cloud Run and Compute Engine, streamlining production workflows and ensuring reliable cloud delivery.
• ● Separated the staging and production environments, and crafted respective workflows, resulting in improved project structure and efficiency.
• ● Implemented basic authentication using Caddy for 5+ serverless apps and one LLM chatbot app, achieving 100% authentication for previously unauthenticated applications.
• ● Analyzed and troubleshooted 50+ production issues using log explorer, metrics collection, thereby enhancing problem-solving skills.
• ● Reduced monthly costs by 8% by configuring metrics in Cloud Run to optimize resource usage and enhance monitoring.
• ● Refactored code to implement FireO ORM in Python to access the database data as objects, thereby reducing the number of lines of code by 30%.
• ● Documented all tasks according to Divio's documentation system.

Apr 2024 – Jul 2024 · 3 mos · Raleigh, North Carolina, United States

• ● Responsible for migration of deep learning models and image segmentation functionalities from "yeastvision" Python library to a React-Django web application, enhancing accessibility and scalability of yeast cell lifecycle analysis for a broader user base.
• ● Utilized Docker to containerize the application, achieving platform independence and enhancing deployment flexibility.
• ● Integrated a Django application with the NC State High Performance Computing (HPC) cluster to accelerate image processing speeds.
• ● Developed a monitoring script using WatchDog to oversee the output directory on the HPC, facilitating timely retrieval of generated output files.
• ● Successfully deployed an application on the NCSU server, utilized by 25 peers at a symposium hosted by NC BioTech in RTP.

Apr 2023 – Jul 2023 · 3 mos

• ● Leveraged Spring Boot to
• ● Develop and implement microservices to build an application that helps in card acquisition for boarding new merchants and servicing existing merchants.
• ● Create preboarding validations by integrating third-party applications into the microservices that help validate if the merchant could be boarded or not thereby increasing the security of the application.
• ● Improve user experience by developing and implementing an email and postback notification system from scratch that helps to trigger a notification at different stages of boarding and servicing a merchant.
• ● Construct a task-specific payload by refining the payload obtained from frontend using Java that is required by the backend teams to validate the downstream calls.
• ● Explored GCP tools like
• ● SpannerDB to store and retrieve the necessary data that was sent from the front end
• ● Log Explore to check the flow of the data across different teams.
• ● Implemented Scheduler in Google Cloud to automate notification processes, significantly boosting system efficiency. This strategic deployment of schedulers resulted in a 15% improvement in notification delivery efficiency.
• ● Participated in integration testing after integrating our application with the backend downstream which helped in reducing the error rate to almost 5% during deployments.
• ● Deployed the code in development and testing environments in Kubernetes engines using Spinnaker and Jenkins.
• ● Actively engaged in sprint activities, such as scrum calls, retrospective meetings, code reviews, deployment processes, and PI planning.

Sep 2021 – Apr 2023 · 1 yr 7 mos

• ● Got trained in cutting-edge technologies like Docker, Kubernetes, AWS, Java and Spring Boot.
• ● Designed JUnit test cases to improve the code coverage to 92% from 30% for various microservices.