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AI Engineer with 5+ years of experience building production-grade agentic AI and LLM applications. Deep hands-on work across RAG, prompt engineering, tool-calling agents, semantic search, and evaluation/guardrails for regulated environments (financial services and healthcare). Experienced in turning business workflows into reliable AI products using Python and modern AI stacks such as LangChain/LangGraph, OpenAI/Azure OpenAI, vector databases, FastAPI, and cloud-native DevOps (Docker, Kubernetes, CI/CD).…AI Engineer with 5+ years of experience building production-grade agentic AI and LLM applications. Deep hands-on work across RAG, prompt engineering, tool-calling agents, semantic search, and evaluation/guardrails for regulated environments (financial services and healthcare). Experienced in turning business workflows into reliable AI products using Python and modern AI stacks such as LangChain/LangGraph, OpenAI/Azure OpenAI, vector databases, FastAPI, and cloud-native DevOps (Docker, Kubernetes, CI/CD).

RAKUL CHETTIPALAYAM KANDAVEL

AI Engineer, Programmer, Software Engineer, +3

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AI Engineer with 5+ years of experience building production-grade agentic AI and LLM applications. Deep hands-on work across RAG, prompt engineering, tool-calling agents, semantic search, and evaluation/guardrails for regulated environments (financial services and healthcare). Experienced in turning business workflows into reliable AI products using Python and modern AI stacks such as LangChain/LangGraph, OpenAI/Azure OpenAI, vector databases, FastAPI, and cloud-native DevOps (Docker, Kubernetes, CI/CD).…AI Engineer with 5+ years of experience building production-grade agentic AI and LLM applications. Deep hands-on work across RAG, prompt engineering, tool-calling agents, semantic search, and evaluation/guardrails for regulated environments (financial services and healthcare). Experienced in turning business workflows into reliable AI products using Python and modern AI stacks such as LangChain/LangGraph, OpenAI/Azure OpenAI, vector databases, FastAPI, and cloud-native DevOps (Docker, Kubernetes, CI/CD).

Available to hire

AI Engineer with 5+ years of experience building production-grade agentic AI and LLM applications. Deep hands-on work across RAG, prompt engineering, tool-calling agents, semantic search, and evaluation/guardrails for regulated environments (financial services and healthcare).

Experienced in turning business workflows into reliable AI products using Python and modern AI stacks such as LangChain/LangGraph, OpenAI/Azure OpenAI, vector databases, FastAPI, and cloud-native DevOps (Docker, Kubernetes, CI/CD).

Skills

Experience Level

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Expert

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Expert

Intermediate

Intermediate

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Beginner

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Beginner

Work Experience

Artificial Intelligence (AI) Engineer – Agentic AI Development at Wells Fargo

August 1, 2024 - Present

Designed and delivered an agentic AI platform for banking operations using Python, LangChain, LangGraph, and Azure OpenAI to automate case handling, policy lookup, and internal knowledge retrieval. Built multi-step agents with tool calling, RAG, and workflow orchestration for consistent, explainable analyst decision support. Developed secure FastAPI services exposing LLM endpoints, retrieval APIs, and agent workflows. Implemented semantic search over internal documents using embeddings, FAISS, pgvector, and PostgreSQL. Added guardrails and output validation for regulated use, and used a LangGraph multi-agent architecture (planning, retrieval, validation, response) for control and traceability. Built document intelligence pipelines for PDFs and other inputs using OCR preprocessing and structured extraction. Created evaluation workflows for grounding and hallucination checks with human-in-the-loop review. Containerized services with Docker and deployed via Kubernetes with CI/CD automatio

Software Engineer at Genpact

January 1, 2021 - November 30, 2023

Built Python and SQL pipelines to ingest, clean, transform, and validate healthcare data for the Fortis Healthcare project. Developed backend services and REST APIs using Flask and FastAPI for internal healthcare applications. Automated document-processing and operational workflows to reduce manual handling. Worked with PostgreSQL and MongoDB to store and query structured and unstructured healthcare records. Implemented ETL workflows integrating data from databases, documents, and internal systems. Added data-quality checks and schema validation to identify incomplete, inconsistent, and duplicate records. Created reusable Python modules for data transformation and database operations, and integrated services with internal and third-party systems via REST APIs. Implemented logging/monitoring, error handling, unit and integration tests, and optimized SQL queries for performance; troubleshot API, data, and pipeline production issues.