Vishaal M.

(MVP) Multi-Agent Orchestration Platform Developement for AI-Driven Automation

Strategic Leadership & Architecture Directed the end-to-end design of AI orchestration architecture integrating specialized AI agents, governance controls, automation workflows, and database systems. Defined AI governance frameworks ensuring secure, compliant, and auditable AI execution across organizational processes. Led AI transformation initiatives focused on operational automation, data intelligence, and enterprise productivity enhancement. Established scalable architecture patterns for modular AI agent communication and orchestration. Agent development life cycle flow - Build - Test - Deploy - Eval - Monitor

Agentic AI Platform Development Designed and implemented advanced Multi-Agent AI systems for orchestrating autonomous and semi-autonomous enterprise workflows. Built Retrieval-Augmented Generation (RAG) frameworks for enterprise knowledge retrieval and contextual AI interactions. Developed Text-to-SQL AI agents enabling natural language interaction with enterprise data systems. Implemented AI evaluation, validation, and execution tracking frameworks to ensure reliability, transparency, and operational monitoring. Created intelligent workflow pipelines integrating multiple enterprise data products and business systems. Multiple Tools development to support the system with human intervention for debugging and approval. Analytical & Reasoning agent to provide information into better reasoning with graphical and chart format Feedback system to improve llm response hallucinations. Skills markdown integration to drive the workflow Intelligently

Governance, Compliance & Risk Management Implemented enterprise data governance workflows including PII detection, sensitive data validation, and compliance enforcement. Introduced human approval and human-in-the-loop review mechanisms before critical AI-driven actions and data sharing

Expert in designing, developing, and deploying scalable ETL pipelines leveraging AWS technologies including AWS Glue, Glue Jobs, Step Functions, CodePipeline, CodeBuild, S3, EC2, CloudFormation, CloudWatch, SNS, and Lambda functions. Proficient in data processing and transformation using PySpark within Glue environments and managing Glue Data Catalog tables for schema management and query optimization via Athena. Experienced in monitoring and alerting of data pipelines through CloudWatch to ensure reliability and prompt incident response. Strong hands-on experience implementing CI/CD workflows for data pipelines and infrastructure automation using GitHub and Bitbucket. Skilled in data ingestion, transformation, and loading from multiple sources such as APIs, databases, and files into target databases including DynamoDB, PostgreSQL, and Snowflake. Skilled in creating and managing AWS S3 buckets with efficient organization of datasets in multiple formats including Parquet, CSV, and JSON for optimized storage and query performance. Comprehensive expertise in building and managing end-to-end cloud infrastructure on AWS including EC2 instances, load balancers, VPCs, and networking components ensuring secure and robust deployment environments. Extensive experience developing RESTful APIs using Python and integrating them seamlessly with AWS services such as API Gateway and Lambda for serverless architecture solutions.