- Developed and maintained multiple ServiceNow applications, enhancing service delivery and operational efficiency for global clients.- Implemented backend services using Python, Django and FastAPI, integrating with various third-party APIs and databases like MySQL and PostgreSQL.- Achieved a 40% performance improvement by optimizing database queries and implementing efficient data caching mechanisms.- Integrated React components into ServiceNow platforms, ensuring seamless and responsive user interfaces.- Leveraged AWS services including Lambda, EC2, S3, and CloudWatch for deploying and monitoring applications, achieving a 99.9% uptime.- Migrated legacy systems to modern cloud-based solutions, reducing infrastructure costs by 30%.- Managed code repositories and implemented CI/CD pipelines using Git, Jenkins, and Docker for automated testing and deployment.- Integrated LangChain and LlamaIndex for natural language processing (NLP) capabilities, enhancing the platform’s ability to analyze and process large volumes of textual data.- Developed custom machine learning models using OpenAI API for predictive analytics and automated decision-making processes.

- Core member of the backend team, responsible for developing and maintaining scalable real estate applications using Python Django.- Enhanced application performance by 45% through code optimization and database indexing.- Implemented data processing workflows using Apache Airflow to aggregate and process large datasets from various real estate platforms.- Integrated AWS services such as SQS, ECS, and DynamoDB to build robust, scalable microservices.- Collaborated with cross-functional teams to design and implement RESTful APIs, facilitating seamless integration with frontend applications.- Conducted code reviews and provided feedback to ensure code quality and adherence to best practices.

- Developed backend services for a medical cost-sharing platform, utilizing Python Django and PostgreSQL.- Implemented secure and efficient payment processing systems, ensuring compliance with industry standards and regulations.Improved system performance by 30% by optimizing database queries and refactoring legacy code.- Collaborated with frontend developers to integrate React components, providing a cohesive user experience.- Utilized Apache Spark for big data processing, enhancing the platform’s data analytics capabilities.- Deployed applications on AWS, leveraging EC2, S3, and CloudWatch for monitoring and scaling.

- Developed and maintained data analytics and machine learning tools using Python, and JavaScript.- Improved data processing speed by 25% through code optimization and parallel processing techniques.- Migrated data across multiple data repositories, enabling large-scale machine learning and data analytics.- Collaborated with data scientists to develop predictive models and integrate them into the Anaconda platform.- Utilized Anaconda Distribution to simplify package management and deployment, facilitating data science and machine learning workflows.- Employed Apache Airflow to orchestrate data workflows and ensure reliable ETL processes.