Software Engineer Computer Science

Amitesh Singh Bais

945-****-*** Email LinkedIn Profile Github Dallas, Texas, US

EDUCATION

●University of Texas at Dallas Dallas, Texas

MS in Computer Science Aug 2024 - May 2026

●BITS PILANI, Hyderabad Campus Hyderabad, India

Bachelors in Engineering Aug 2018 - May 2022

Skills

Frameworks/Databases: Django, ExpressJS, NodeJS, ReactJS, NestJS, MYSQL, MongoDB, PostgreSQL, Redis Languages: Java, HTML/CSS, C/C++, JavaScript, TypeScript, Python Cloud skills: AWS: EC2, Kinesis, Lambda, S3, Polly, ECS, Cloudwatch, Step function, Bedrock Miscellaneous: Elastic Search, Redis, AG Grid, Docker, GraphQL, Celery, Microservices, Tanstack, Git, NLP, Numpy, Pandas WORK EXPERIENCE

Terrafinn technologies Pvt Ltd.Remote

Software Engineer Aug 2023 - Jul 2024

●Designed and implemented REST APIs using TypeScript/JavaScript/NodeJS and MongoDB (NoSQL) to validate and update financial metrics data via CSV uploads, streamlining high-volume metric updates for analysts, improving efficiency by 15%.

●Implemented GraphQL queries and designed resolvers to efficiently manage data retrieval and mutations, minimizing redundant fetching across multiple endpoints and improving performance and scalability by 20%.

●Developed a text-to-speech feature by integrating AWS Polly with AWS Lambda to generate audio for articles, storing outputs in S3, and enhancing client engagement by 25%.

●Built reusable UI components using NextJS, TypeScript, React, Tailwind CSS, Tanstack for various features resulting in ensuring consistency, scalability and a seamless user experience. RetainIQ Pvt Ltd.Banglore, India

Software Engineer Jun 2022 - Jul 2023

●Designed and monitored REST APIs in Python/Django & SQL for various application features enabling clients to generate customizable marketing campaigns, to boost their campaign revenue by 20%.

●Created a robust service using AWS Kinesis to pull clickstream data and store it across multiple levels of data storage, including PostgreSQL, Elasticsearch, and MongoDB, ensuring efficient analytics and enabling real-time insights into user behavior.

●Designed and developed a scalable marketing campaign system applying microservices architecture integrating AWS STEP function and AWS Lambda function increasing customer retention by 30%.

●Implemented scripts in Python to cache results for high processing operations using Redis to decrease latency of main content delivery APIs by 15%.

RetainIQ Pvt Ltd.Banglore, India

Software Engineer Intern Jul 2021 - May 2022

●Built a Shopfiy app from scratch utilizing ExpressJS, NodeJS, React, Docker and hosted the app using AWS EC2, ECS delivering the company's main product gaining client attraction by 40%.

● Implemented REST APIs to handle the OAuth 2.0 app installation process, enabling secure authentication and authorization, while integrating JWT tokens for efficient, stateless user session management to enhance security and access control.

●Designed database relations and implemented queries in SQL applying normalization and indexing strategies to store/retrieve data, improving efficiency by 30%.

●Developed a cron job using NodeJS/JavaScript to fetch data from multiple ecommerce stores at regular intervals via Shopify APIs, automating data retrieval and reducing manual effort by 35%, while processing over 10,000 records daily. Project Experience

Domain specific assistant - AI

●Built an AI assistant to generate contextual answers for a domain specific knowledge base using AWS Bedrock as a foundational LLM model and RAG techniques.

●Implemented a document ingestion pipeline that generates vector embeddings of semantic data chunks and stores in ElasticSearch, enabling highly efficient and context-aware data retrieval.

●Enhanced prompt responses by augmenting them with contextual information fetched through K-Nearest Neighbors (KNN) search from the vector database, ensuring accurate, relevant answers. Sentiment Analysis of Tweets

●Developed a sentiment analysis NLP model using transformers library, fine-tuning the pre-trained BERT model for multi-class classification of tweets into multiple categories achieving an accuracy of over 80%.

●Used pandas for data preprocessing, numpy for numerical computations, ensuring a robust model training and testing. Phrase Matching Classification

●Built an NLP model for phrase similarity matching by fine-tuning the deberta model using Hugging Face's Trainer API.

●Achieved a Pearson correlation coefficient of 0.82 and consistently improved performance across epochs on validation data. Certifications

●Cloud Practitioner: Amazon Web Services (AWS) - see credential Jan 2025 - Jan 2028

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