• Developed an efficient Query Builder for Elasticsearch, enhancing query performance by fine-tuning nodes.• Designed and implemented an abstract API base using FastAPI for a petabyte-scale system with robust RBAC andmicroservice architecture, reduced new API service creation time from 1 day to 30 minutes while leading a team of 5.• Developed the UI using React with RBAC and custom components, reducing page load time by 40% through parallelizingAPI requests and user-customizable design.• Integrated efficient logging, profiling, and auditing for every request using Loki, pyinstrument, and Pulsar.• Building a data platform using Kafka, Data Lake, Prometheus & Grafanafor logs & metrics with efficient Data Pipelinesand Apache Superset for data visualization• Created a test framework with pytest, achieving 98% coverage using real dependencies and zero-mocking.• Optimized Docker build process, reducing build time from 5min to 10s through layers and caching. Implemented Helmcharts for Flux CD with Kubernetes• Enhanced application security with Keycloak, optimizing the authentication process from 1s to under 200ms.

• Optimized API response time by over 85%, from 20-30 seconds to under 3 seconds, utilizing Redis cache• Created a chatbot for users with Google VertexAI and Google Kubernetes Engine to interact with a given set of data• Optimized code with OOP principles & reusability, types & validations with Pydantic, and reduced codebase by 10%• Improved code coverage from 68% to 83%* and upgraded the entire test suite to create robust test cases with pytest• Reduced the patient onboard time by 80% with self-signup using Twilio

• Developed a data platform using Kafka, Spark, Snowflake for analytics, and Grafana, Prometheus for logs, metrics.• Designed, managed, and scaled a Kubernetes cluster for microservices orchestration

• Optimized API response time by 80% through caching.• Led end-to-end development of a highly available MERN application, integrating Payment Gateway.• Dockerized a GDPR-compliant Django application with Node.js backend, serving 10k+ students, and implemented CI/CD with AWS CodePipeline.• Designed, architected, and implemented a Notification service, along with a mailing service, that significantly improved response time from 4 seconds to under 100 milliseconds using multithreading.• Applied Genetic Algorithms (ML) to craft complex schedules for a 10,000+ students under challenging conditions.

• Developed Voicebot using Twilio, GCP (Google Cloud Platform) Speech to text, and text-to-speech APIs.• Worked in back-end development and created REST APIs using NodeJS and Wit.ai for NLP• Handled 200M+ documents in MongoDB, efficiently• Worked with ReactJS and also worked with Figma and static pages with responsive design• Worked with Mocha Chai, Jest, and React testing library for Unit testing• Worked in process of transferring leads from Chatgen to the client’s Salesforce sandbox.• Worked in R & D and researched chatbot feature development and improvements