Available for AI / Generative AI roles

AI Engineer architecting enterprise RAG and multi-agent systems.

6+ years from ETL and data engineering to production Generative AI. I build RAG pipelines, autonomous agent platforms, and LLM-powered services for Banking, Healthcare, and Technology, all cloud-native on Azure and GCP.

Vishal Yadav Chatharasi
About

Turning language models into systems the enterprise runs on

I'm an AI Engineer with 6+ years of progressive experience, from ETL and data engineering into architecting enterprise Generative AI systems. I build production-grade RAG pipelines, multi-agent orchestration platforms, and LLM-powered applications across Banking, Healthcare, and Technology.

The part I care about is what happens after the prototype: hybrid retrieval that stays grounded, agent workflows that can be reasoned about, and Azure-first infrastructure with governance, evaluation, and observability once real traffic arrives.

Location
New York, NY, US
Focus
RAG, multi-agent systems, MLOps
Education
M.S. Computer Software Engineering
Cloud
Azure, GCP, AWS
Status
Open to new roles
Stack

Tools I work with

Core stack

Python
FastAPI
AIOpenAI
Claude
LangChain
LGLangGraph
AzAzure
AISAzure AI Search
Hugging Face
Docker
k8sKubernetes
tfTerraform
Google Cloud
SNSnowflake
PostgreSQL
MLfMLflow
Pandas
NumPy
Git
TypeScript

Detailed breakdown

AI & LLMs

GPT-4 / 4.5LLaMA 2 / 3ClaudeHugging Face Transformers Microsoft Agent Development Kit (ADK)Azure AI FoundryOpenAI Agent SDKLangChain LangGraphMulti-Agent SystemsAutonomous AI AgentsAI Workflow Orchestration

RAG & Search

RAG PipelinesAzure AI SearchOpenAI Vector StoreVector DBs Hybrid RetrievalMCP / FastMCP

Languages, Frameworks & Libraries

PythonSQLTypeScriptREST APIs FastAPIFlaskGraphQLpytest NumPyPandasScikit-learnTensorFlow PyTorch

ML & Statistics

RegressionClassificationClusteringFeature Engineering Model EvaluationHyperparameter TuningCross-ValidationHypothesis Testing A/B TestingPredictive Modeling

Cloud & Infrastructure

Azure (Functions, App Service, SQL, Key Vault)GCP (BigQuery, Pub/Sub, Cloud Storage)AWSTerraform DockerKubernetes

Data & ETL

Informatica PowerCenter / IDQKafka (Confluent)AirflowNode.js MongoDBOracleSnowflakeNeo4j

Databases

PostgreSQLMySQLpgvectorFAISS Vector Databases

MLOps & Tools

MLflowPromptfooLiteLLMCI/CD Git / GitHubJupyterVS CodeCursor JiraAgile/Scrum

Visualization & BI

TableauPower BIMatplotlibAdvanced Excel
Work

Selected projects

A selection of AI, Web3, and developer-tooling projects, all open source on GitHub.

Impact

Shipped AI artifacts

Production systems delivered inside enterprise engagements: the work behind the roles below.

Enterprise RAG Pipeline

LangChain · Embeddings · pgvector

Document ingestion, chunking, metadata tagging, semantic search, and retrieval optimization, improving retrieval relevance and reducing incomplete responses across enterprise knowledge at Humanity Labs.

Wealth-Management Agentic Workflow

Amazon Bedrock · Agentic AI

Converted manual operations into autonomous workflows that navigate steps, process documents, update tracking files, trigger system actions, and produce auditable outputs for stakeholder review.

Healthcare Clinical AI Prototype

Azure OpenAI · GPT-4

Real-time speech-to-text front end, a 180-entity clinical extraction workflow, citation-aware response generation, and confidence scoring, delivered end to end at Crayon.

Insurance & Legal RAG Chatbots

GPT · RAG · Citations

Citation-aware answers for internal employee knowledge workflows and external website inquiry experiences, with custom retrieval logic and conversational UX.

AI Backend Services

Python · FastAPI

APIs powering document ingestion, semantic search, response generation, and workflow execution for production AI application features.

Experience

Where I have worked

Gen AI Engineer

Jan 2026 – Present

Wells Fargo · Charlotte, NC

  • Architected a scalable Generative AI platform with RAG pipelines, LangGraph agent orchestration, and Azure OpenAI for enterprise knowledge retrieval and autonomous task execution.
  • Built autonomous AI agents on orchestration frameworks aligned with the Microsoft Agent Development Kit (ADK), enabling contextual reasoning, workflow automation, and operational monitoring.
  • Engineered end-to-end RAG (document ingestion, chunking, OpenAI embeddings, vector storage, and hybrid retrieval) for grounded semantic Q&A at scale.
  • Developed a multi-stage Python ETL pipeline on Azure Functions for sitemap discovery, HTML/PDF extraction, and concurrent processing with metadata in Azure SQL.
  • Built FastAPI services and an MCP/FastMCP HTTP gateway on Azure App Service to standardize governed tool access for LLM agents.
  • Optimized API performance and reliability through async processing, vector store integration, and SRE/SLO-aligned monitoring.
  • Deployed Azure-first infrastructure (Functions, Azure SQL, TypeScript, Terraform, Key Vault) with scheduled crawls and delta updates across staging and production.

Data Scientist / AI Engineer

Jun 2024 – Dec 2025

FedEx · Memphis, TN

  • Designed and deployed a distributed multi-agent AI platform for Competitive Intelligence, integrating SharePoint, external feed APIs, web search, and Excel with text/image extraction pipelines.
  • Built enterprise Agentic AI solutions with LangGraph, the OpenAI Agent SDK, and Azure AI services for reasoning, task orchestration, and contextual decision-making.
  • Developed enterprise search and RAG pipelines on Azure AI Search (hybrid vector + keyword) across SharePoint, Teams, APIs, and web sources for real-time semantic Q&A.
  • Architected multi-agent workflows for autonomous retrieval, planning, reasoning, and execution over large enterprise datasets and external intelligence sources.
  • Delivered a Snowflake-backed GTM analytics assistant using FastAPI, GraphQL, and LangGraph agents for autonomous SQL generation, execution, and streaming responses.
  • Implemented LLM governance, observability, and evaluation frameworks (MLflow, Promptfoo) for agent monitoring, safety validation, and model evaluation.
  • Managed Azure AI infrastructure, API integrations, LiteLLM routing, RBAC, and PII/PHI protection for secure enterprise deployment.

Jr. Data Analyst

Mar 2019 – Aug 2023

Amazon · India

  • Architected enterprise-scale data platforms for reliable ingestion, transformation, and delivery of high-volume customer data.
  • Designed end-to-end ETL frameworks with Informatica PowerCenter and IDQ, built for scalability, fault tolerance, and data-quality governance.
  • Led real-time streaming architecture on Kafka (Confluent) for CDC pipelines from MDM to downstream systems, integrated with GCP Pub/Sub and BigQuery.
  • Automated complex workflows with Python and Airflow; led the IDQ platform upgrade (10.2 → 10.4) for a 12% performance improvement.
  • Defined data architecture standards covering data modeling, pipeline orchestration, and metadata management.
Education

Education & certifications

M.S., Computer Software Engineering

Aug 2023 – May 2025

Cleveland State University · Cleveland, OH

Certifications

Oracle Certified Foundations Associate Oracle Foundations-level Oracle certification.
Microsoft Certified: Azure AI Fundamentals Microsoft AI workloads, machine learning, computer vision, NLP, and generative AI on Azure.
Introduction to Generative AI Google Cloud Generative AI fundamentals, large language models, and responsible AI practice.
Generative AI with Large Language Models DeepLearning.AI & AWS LLM lifecycle: pre-training, fine-tuning, RLHF, and deployment at scale.
AI Fluency: Framework & Foundations Anthropic Completed alongside Claude 101, Claude Code 101, Claude Code in Action, and Introduction to Claude Cowork.
Contact

Let’s work together

Open to AI / Generative AI engineering roles. Email is the fastest way to reach me.