Nikhil Sharma

I have designed and developed a Generative AI–powered document intelligence platform that enables natural language querying, summarization, and insight extraction from unstructured financial and regulatory documents. Also, built a Retrieval-Augmented Generation (RAG) pipeline with document ingestion, semantic chunking, embeddings, and vector search to deliver source-grounded answers using LLMs. Implemented APIs for real-time question answering and explanation generation for tax and compliance use cases. Added guardrails, metadata filtering, and citation support to improve accuracy and reduce hallucinations. Optimized retrieval performance and scalability using vector databases and asynchronous services, transforming static calculators and guides into explainable AI assistants.

I studied Artificial Intelligence and Machine Learning from lambton college, Toronto. Learning about the Introduction to Artificial Intelligence upto the deployment of a machine learning model to cloud like AWS (Amazon Sagemaker) made this course different and upto Date. Looking forward, I am currently working on different AWS Services.

Worked as a Software Developer at Dotsquares, my Job roles include working across various python codes, handling different errors in Django codes, and working with AWS services such as S3, EC2, VPC etc. It also includes working with a lot of data from various sources, making various reports and summarizing various findings and recommendations. I collaborated with various teams to define data requirements and data processes.

I have developed web applications with the focus of writing clean code in programming. I have worked across various edge technologies such as Python programming, Django framework and AWS. I was working with the web development part also along with the deployment of apps into AWS infrastructure. I often collaborated with various teams to design and implement scalable, robust solutions. Along with this, I managed the infrastructure and monitored the system performance by the use of various tools like Docker, Jenkins and Terraform. Around this time, I was also able to get knowledge of the cloud platforms such as AWS.

I have worked across different projects which are related to the data science such as a recommendation system along with the deployment of the machine learning model into the cloud technologies such as Amazon Web Services [AWS]. With previous experience in django framework, I got the exposure to analyze the software Development as well as the Data Science part of any project. Ensuring the smooth process of deployment along with the minimum downtime.