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We taught silicon to speak. Now it’s asking who it is. So am I.
🎯
We taught silicon to speak. Now it’s asking who it is. So am I.
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Achievement: Pair Extraordinairex2Achievement: Pull Sharkx2Achievement: YOLOAchievement: Quickdraw

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MukundaKatta/README.md
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Portfolio LinkedIn X Email


  8+ years building production systems at Fortune 100 scale
  Former SDE at Amazon Web Services  •  Currently at Southwest Airlines
  Deep expertise in ML systems, distributed architectures, and full-stack engineering

Impact at a Glance

78%
Infrastructure cost reduction
SageMaker → Bedrock migration 		600x
Retrieval latency improvement
ML prediction system 		30K+
Knowledge base entries
9-stage agentic RAG pipeline 		370+
Unit tests & evaluations
Production ML systems

What I Build

 ML Systems           Fault prediction, embedding pipelines, model evaluation, cost-optimized inference
 Agentic AI           RAG pipelines, LangGraph workflows, query routing, hallucination detection
 Cloud Infrastructure AWS (Bedrock, SageMaker, ECS, OpenSearch), GCP, Azure, Kubernetes, Terraform
 Full-Stack           React/TypeScript + Java/Python backend APIs, CI/CD, zero-downtime deployments

Experience

Role Company Duration
AI/ML Engineer Southwest Airlines Aug 2025 — Present
AI/ML Engineer GPS IT Solutions Jun 2024 — Aug 2025
Software Development Engineer Amazon Web Services (AWS) Aug 2022 — May 2024
Data Engineer Cigna Jan 2022 — Aug 2022
Software Engineer American Express Feb 2017 — Dec 2020
Highlights

Southwest Airlines — AI/ML Engineer

  • Architected ML fault prediction system for aircraft maintenance — 5 prediction types, 10K+ records, sub-second retrieval
  • Led SageMaker → Bedrock migration: 78% cost reduction ($1,740→$371/mo), 600x latency improvement
  • Designed 9-stage agentic RAG pipeline (LangGraph, Bedrock Nova Pro/Micro, FAISS + BM25) over 30K+ KB entries

GPS IT Solutions — AI/ML Engineer

  • Built GPT-4 + RAG content generation platform with compliance validation, reducing production time by 40%
  • Designed AI model risk governance framework with 23 automated evaluation tests achieving regulatory compliance
  • Architected FastAPI microservices with FAISS/Pinecone vector search on Kubernetes

Amazon Web Services (AWS) — Software Development Engineer

  • Built and shipped features for AWS Application Manager (Systems Manager) serving enterprise customers globally
  • Owned full-stack delivery: React/TypeScript frontend + Java/Python backend APIs with operational excellence
  • Designed CI/CD and IaC patterns enabling zero-downtime deployments at enterprise scale

Cigna — Data Engineer

  • Led end-to-end migration of healthcare data pipelines from on-prem to AWS (Glue, PySpark)

American Express — Software Engineer

  • Developed Python backend services and RESTful APIs for enterprise platforms handling high-volume transactions at scale

Featured Projects

Karna — AI Agent Platform

Self-hosted AI assistant with 7 messaging channels (Telegram, Slack, Discord, WhatsApp, SMS, iMessage, Web), extensible plugin SDK, semantic memory, and voice. TypeScript monorepo with Next.js dashboard and React Native mobile app.

TypeScript • Node.js • Next.js • Supabase • WebSocket • pgvector

MCPForge — MCP Server Builder

CLI toolkit to scaffold, test, and deploy Model Context Protocol servers in minutes. Zero-config defaults with progressive complexity disclosure. Built for the Anthropic MCP ecosystem.

TypeScript • MCP • CLI • Developer Tools

AgentRAG — Modular RAG Pipeline

Provider-agnostic RAG framework with pluggable vector stores, chunking strategies, and retrieval methods. Designed for agentic workflows with clean API boundaries.

RAG • Vector Search • Embeddings • TypeScript

Astra Agent — AI Agent Runtime

Standalone AI agent runtime with tool execution, context management, and multi-model routing. Foundation for building autonomous AI assistants with structured tool use.

TypeScript • LLM Orchestration • Tool Use • Agents
More Projects
Project Description
Sadhak AI-powered job search command center — automated evaluation, resume tailoring, application tracking
Chetana AI consciousness research platform — 14 indicators from 6 scientific theories
Prithvi Container security scanner — vulnerability detection, compliance checks, Docker audits
Amogha Cafe Full-stack Firebase restaurant platform — real-time ordering, QR dine-in. Live
RNHT Temple community platform — events, donations, priest scheduling
Vimana Self-orchestrating AI — autonomous cloud infrastructure provisioning
AgentBench Agent evaluation and benchmarking suite
AgentMem Pluggable memory management for AI agents
LLM Bench CLI CLI for benchmarking local LLMs — speed, throughput, quality
TokenWise Token usage optimization across providers

Education

University of Central Missouri — M.S. in Big Data Analytics and Information Technology (Jan 2021 — May 2022)

SRM University — B.Tech in Mechanical Engineering (2012 — 2016)

Certifications

Anthropic

MCP Advanced Claude with Bedrock Claude with Vertex AI Intro to MCP Claude Code Building Claude API Agent Skills Subagents AI Fluency Claude 101

AWS

AWS GenAI Apps AWS AI Solutions AWS AI Fundamentals Amazon Q

Cloud & Infrastructure

Terraform GCP Vertex AI Agent

Stanford / Wharton

ML Stats Business Analytics Customer Analytics People Analytics

Microsoft

GenAI for Devs GitHub Copilot Copilot PM

LinkedIn Learning

Deep Learning TensorFlow NLP Python Apache Spark

Tech Stack

TypeScript Python JavaScript Java Go React Next.js Node.js Claude OpenAI AWS GCP Snowflake Supabase PostgreSQL Docker Kubernetes Terraform FastAPI Redis Apache Airflow Apache Spark LangChain

GitHub Stats

  


Open to opportunities — Senior AI/ML Engineer • GenAI Platform Engineer • Software Engineer

mukunda-ai.vercel.app • Las Vegas, NV


Profile Views

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    A lightweight Python toolkit to monitor, test, and benchmark MCP (Model Context Protocol) server health, latency, and connectivity. Built for the growing MCP ecosystem.

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    Minimal Python toolkit for creating MCP servers from plain functions using decorators

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