Naveen Bisht

AI Engineer

https://talent.gravityer.com/naveen-bisht

India

Key Strengths

Demonstrated interest in AI/ML through multiple personal projects like SKF.ProductAssistant, repo-lens-ai, talentrag-ai, and bedrock-aws-cloude-app.
Experience with various cloud platforms including Azure (Azure Functions, Azure OpenAI) and AWS (Amazon Bedrock, AWS Lambda, AWS Textract).
Exposure to different programming languages relevant to AI engineering such as Python, C#, and JavaScript.
Familiarity with RAG systems and vector embeddings as shown in the talentrag-ai project.

Cultural & Operational Fit

Cultural Fit Analysis

The candidate's projects demonstrate a strong inclination towards personal learning and exploration of new technologies, particularly in the AI domain. This self-driven approach could be a good cultural fit for an innovative team. However, the lack of professional experience or team-based projects makes it difficult to fully assess collaboration and broader cultural alignment.

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Projects

MultiAppSingleContainer

June 10, 2026 – Present

BFF (POC) with multiapp with single container

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repo-lens-ai

April 19, 2026 – Present

A serverless AI-powered tool that analyzes GitHub repositories and provides structured insights, issues, improvements, and scoring. Built using Azure Functions, Azure OpenAI, and React.

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bedrock-aws-cloude-app

April 12, 2026 – Present

Designed and developed a serverless AI chatbot leveraging Amazon Bedrock (Claude), AWS Lambda, and React. Showcases cloud-native architecture and generative AI integration.

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talentrag-ai

April 11, 2026 – Present

TalentRAG AI is a lightweight Retrieval-Augmented Generation (RAG) system designed to enable intelligent querying over structured enterprise data. The solution transforms traditional SQL-based datasets into semantically searchable knowledge using vector embeddings and AI-driven reasoning.

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SKF.ProductAssistant

March 15, 2026 – Present

AI Product Assistant built with C#, Azure Functions, Semantic Kernel, Azure OpenAI and Redis caching.

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React-Learning

October 23, 2025 – November 18, 2025

React-Learning — GitHub repository

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DesignPatternsDemo

September 9, 2025 – September 12, 2025

DesignPatternsDemo — GitHub repository

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SmartMarketPlaceMicroserivces

August 8, 2024 – August 14, 2024

SmartMarketPlaceMicroserivces — GitHub repository

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Ocelot.Demo

August 6, 2024 – September 4, 2025

Ocelot.Demo — GitHub repository

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aws-textract-highlight

October 25, 2023 – September 4, 2025

aws -text exract api integration with image highlighting

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Key Strengths

Demonstrated interest in AI/ML through multiple personal projects like SKF.ProductAssistant, repo-lens-ai, talentrag-ai, and bedrock-aws-cloude-app.
Experience with various cloud platforms including Azure (Azure Functions, Azure OpenAI) and AWS (Amazon Bedrock, AWS Lambda, AWS Textract).
Exposure to different programming languages relevant to AI engineering such as Python, C#, and JavaScript.
Familiarity with RAG systems and vector embeddings as shown in the talentrag-ai project.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit

Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.

Naveen Bisht

Key Strengths

Cultural & Operational Fit

Top Skills

Skills

Projects

Key Strengths

Cultural & Operational Fit