Abhishek C.

Key Skills

Software

Other

Top Subject Matter

Enterprise search

generative AI for knowledge retrieval

Generative AI chatbots

Top Data Types

Text

Document

Image

Top Task Types

Prompt + Response Writing (SFT)

Question Answering

Freelancer Overview

Senior Software Developer [Generative AI] - Tech Mahindra [Makers Lab]. Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Computer Applications, Maharaja Ranjit Singh Indore (2017) and Post Graduate Diploma in Management (Finance), Welingkar Institute of Management Development and Research (2022). AI-training focus includes data types such as Text and Document and labeling workflows including Prompt + Response Writing (SFT) and Question Answering.

Labeling Experience

Senior Software Developer [Generative AI] - Tech Mahindra [Makers Lab]

OtherTextPrompt + Response Writing (SFT)

Built an AI-powered enterprise search scratchpad that enabled natural-language querying over enterprise databases and assets using prompt engineering and few-shot learning techniques. Skipped redundant LLM calls for UI filters and auto-suggestions to improve response quality and system efficiency. Extended the architecture conceptually to unify chat-based access across heterogeneous enterprise sources such as CRMs for scalable deployment. • Prompt engineering for enterprise search queries • Few-shot learning to improve retrieval responses • Performance optimization by reducing unnecessary LLM calls • Extending unified chat-based access across data sources

2024 - Present

Senior Software Developer - Indegene + Bitcot

OtherDocumentQuestion Answering

Developed a Generative AI Chatbot Creator Platform that allowed users to build custom chatbots capable of answering queries using multiple knowledge sources. Implemented a RAG-based product recommendation and enterprise search experience by integrating vector databases and retrieval components for more accurate, context-aware responses. Enabled ingestion and retrieval over varied document formats including images, text files, CSV/JSON, and PPT, plus database-backed knowledge sources. • Building query-answering chatbots with multi-source knowledge • RAG implementation using LangChain with vector stores (ChromaDB/PGVector) • Enterprise search over 1,000+ PDFs via AWS Kendra • Supporting knowledge inputs across images and common file formats

2023 - 2024

Education

Work History