AI Engineer with 6 years of experience designing and deploying enterprise AI solutions using Generative AI, Large Language Models, Machine Learning, Deep Learning, NLP, and MLOps. Experienced in building AI assistants, intelligent automation platforms, document intelligence systems, recommendation engines, and scalable inference services using modern AI frameworks and cloud platforms.
Expertise & skills
Selected projects
Healthcare Claims Document Intelligence
Developed an AI platform to analyze healthcare claim documents, extract key information, and generate concise summaries.
- Built document ingestion pipelines.
- Implemented vector search with RAG.
- Integrated enterprise APIs.
- Optimized prompt templates.
- Improved document processing efficiency.
Retail Price Optimization Platform
Built ML models to recommend optimal product pricing using demand and competitor data.
- Developed forecasting models.
- Performed feature engineering.
- Automated retraining pipelines.
- Published scalable prediction APIs.
Enterprise Policy Knowledge Assistant
Created an AI assistant for answering organizational policy questions using internal documentation.
- Indexed enterprise documents.
- Implemented semantic retrieval.
- Built secure REST APIs.
- Enhanced response quality through prompt engineering.
Streaming Content Recommendation Engine
Developed an AI recommendation system for personalized movie and TV content suggestions.
- Designed recommendation algorithms.
- Optimized ranking models.
- Built inference APIs.
- Improved personalization accuracy.
Core competencies
Certifications
- Microsoft Certified: Azure AI Engineer Associate
- AWS Certified AI Practitioner
- Generative AI with Large Language Models
- Hugging Face NLP Professional Certificate
- TensorFlow Developer Certificate
Education
Bachelor of Engineering (Artificial Intelligence & Data Science)
Gujarat Technological University
Achievements
- Delivered 20+ enterprise AI solutions across multiple industries.
- Reduced document analysis effort by 75% using AI automation.
- Improved recommendation accuracy by 30% through model optimization.
- Developed reusable AI services for enterprise applications.
- Successfully deployed production AI workloads on Kubernetes.
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