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I'm a dynamic and results-driven AI Engineer with a solid foundation in Computer Science. I build, test, and deploy enterprise-grade Agentic AI applications, orchestrate multi-agent workflows, design RAG pipelines, and implement guardrails to keep models safe and reliable. I excel at writing clean Python for data processing, tool integration, and automation, and I collaborate with cross-functional teams to turn GenAI research into production features. I value observability, memory management, and scalable back-end solutions, and I'm excited to explore new GenAI technologies and architectures like MCP and A2A.…I'm a dynamic and results-driven AI Engineer with a solid foundation in Computer Science. I build, test, and deploy enterprise-grade Agentic AI applications, orchestrate multi-agent workflows, design RAG pipelines, and implement guardrails to keep models safe and reliable. I excel at writing clean Python for data processing, tool integration, and automation, and I collaborate with cross-functional teams to turn GenAI research into production features. I value observability, memory management, and scalable back-end solutions, and I'm excited to explore new GenAI technologies and architectures like MCP and A2A.

Gollapothu Yashdeep Chandra Sai

AI Engineer, Data Scientist, Full Stack Developer, +2

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I'm a dynamic and results-driven AI Engineer with a solid foundation in Computer Science. I build, test, and deploy enterprise-grade Agentic AI applications, orchestrate multi-agent workflows, design RAG pipelines, and implement guardrails to keep models safe and reliable. I excel at writing clean Python for data processing, tool integration, and automation, and I collaborate with cross-functional teams to turn GenAI research into production features. I value observability, memory management, and scalable back-end solutions, and I'm excited to explore new GenAI technologies and architectures like MCP and A2A.…I'm a dynamic and results-driven AI Engineer with a solid foundation in Computer Science. I build, test, and deploy enterprise-grade Agentic AI applications, orchestrate multi-agent workflows, design RAG pipelines, and implement guardrails to keep models safe and reliable. I excel at writing clean Python for data processing, tool integration, and automation, and I collaborate with cross-functional teams to turn GenAI research into production features. I value observability, memory management, and scalable back-end solutions, and I'm excited to explore new GenAI technologies and architectures like MCP and A2A.

Available to hire

I’m a dynamic and results-driven AI Engineer with a solid foundation in Computer Science. I build, test, and deploy enterprise-grade Agentic AI applications, orchestrate multi-agent workflows, design RAG pipelines, and implement guardrails to keep models safe and reliable.

I excel at writing clean Python for data processing, tool integration, and automation, and I collaborate with cross-functional teams to turn GenAI research into production features. I value observability, memory management, and scalable back-end solutions, and I’m excited to explore new GenAI technologies and architectures like MCP and A2A.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Intermediate

Intermediate

Work Experience

Independent AI Researcher at Independent AI Researcher (Self-employed)

January 1, 2026 - June 1, 2026

Architected and deployed multi-agent workflows using LangGraph and Google ADK, improving task execution accuracy and reducing latency in complex reasoning chains. Developed and optimized advanced RAG pipelines utilizing Milvus DB and FAISS for high-dimensional vector search. Engineered production-ready Python scripts following strict OOP guidelines to handle tool coding and real-time data processing. Implemented AI observability and safety layers using Phoenix and Guardrails AI to reduce LLM hallucinations and ensure compliance. Integrated long-term memory solutions leveraging Mem0 for personalized, context-aware agent interactions. Explored and prototyped emerging GenAI technologies, including MCP and A2A frameworks. Built and maintained scalable backend services using FastAPI and interactive data tools using Streamlit. Designed efficient data pipelines with Pandas and NumPy for large-scale datasets.