🤖 Hands-on experience with LLMs, RAG, foundation models, prompt engineering, semantic search, vector embeddings, and AI-powered automation.

🚀 Built an AI-powered semantic search system using OpenAI embeddings and pgvector, processing and searching across millions of podcast episodes.

🔗 Integrated AI models and platforms including Amazon Bedrock, Amazon Q, OpenAI API, OpenAI Embeddings, and Anthropic Claude API into production workflows.

🧩 Worked with AI agents, MCP (Model Context Protocol), tool use/function calling, and agentic automation to connect AI with infrastructure, monitoring, and operational systems.

⚡ Automated AI and data pipelines, improving processing efficiency by approximately 30% through AI-assisted development and automation workflows.

☁️ Strong experience with AWS and cloud infrastructure, including EC2, S3, Lambda, IAM, VPC, CloudWatch, SageMaker, and Kendra, along with Docker, Kubernetes, Terraform, and CI/CD.

🔍 Experienced with vector search technologies including pgvector, Amazon OpenSearch, Apache Solr, and Pinecone, along with large-scale data processing and web crawling systems.

💡 Solutions-oriented engineer with experience combining AI/ML, cloud infrastructure, APIs, and automation to build scalable and intelligent systems.