Walmart Labs Production · 2023

550M-SKU Replenishment Platform

Designed a data platform processing 550 million SKUs with integrated ML models for inventory forecasting. Built on Apache Spark and GCP, powering Walmart e-commerce replenishment decisions at scale.

Apache Spark Java GCP Airflow BigQuery ML Models
Personal Research Prototype · 2024

AI Developer Assistant

A prototype combining LLM prompt engineering, vector database retrieval, and knowledge graphs for context-aware code suggestions and debugging. Explores RAG patterns and agent architectures.

LLM Vector DB Knowledge Graph RAG Python
Open Source Architecture POC

OmniMart Ratings & Reviews API

Production-grade ratings and reviews service in Go. Hexagonal architecture, dual-tier API (public + moderation), cursor pagination, idempotent writes, swappable SQLite / in-memory backends. Built to show how I think about systems design.

Go SQLite REST API Hexagonal Arch

2023 — Present

Sunnyvale, CA

Software Engineer III

Walmart Labs
  • Shipped a production LLM chatbot (Google Vertex AI + BigQuery) converting business questions to SQL — serving replenishment teams at ~100 queries/day with zero SQL knowledge required
  • Designed a data platform processing 550M SKUs with integrated ML models for inventory forecasting
  • Built scalable Spring Boot API services; data pipelines with Apache Spark, Airflow, and GCP
JavaApache SparkVertex AIBigQueryPythonGCP

2022 — 2023

Scottsdale, AZ

Software Engineer II — Big Data

Choice Hotels
  • Optimized real-time analytics and live data stream processing on AWS (Airflow, EMR, Athena, EC2)
  • Automated legacy system migration, improving data reliability across the analytics platform
AWSEMRAthenaAirflow

2020 — 2022

Scottsdale, AZ

Software Engineer

Early Warning (Zelle)
  • Enhanced the Zelle payment backend processing high-value financial transactions using Java Spring Boot, Docker, and REST APIs
  • Supported AWS cloud infrastructure; implemented notification services enabling AI-driven product features
JavaSpring BootDockerAWS

2019

Phoenix, AZ

Data Science Intern

American Express
  • Built an end-to-end ML pipeline for credit card offer prediction — feature engineering, model optimization, and automated performance reporting
PythonScikit-learnML Pipeline

AI & LLM Engineering

  • LLM Integration & Prompt Engineering
  • Agent Architectures & Workflows
  • Vector Databases · RAG
  • Knowledge Graphs
  • Google Vertex AI
  • Model Fine-tuning
  • TensorFlow · PyTorch · Scikit-learn

Data & Distributed Systems

  • Apache Spark · Hadoop
  • Airflow · BigQuery · SQL
  • Streaming & Batch Pipelines
  • ML Model Integration
  • Data Mining

Backend Engineering

  • Java · Python · Go · Scala
  • Spring Boot · REST APIs
  • Docker
  • PostgreSQL · MySQL · SQLite
  • System Design & API Architecture

Cloud & Infrastructure

  • GCP (Vertex AI, BigQuery, Airflow)
  • AWS (EC2, EMR, Athena, S3)
  • Linux · Git

I'm a senior software engineer with seven years of experience shipping production systems across fintech, hospitality, and large-scale e-commerce. At Walmart, I own a data platform processing 550 million SKUs and built the team's first production LLM integration — a natural-language query interface that lets business stakeholders ask plain-English questions against BigQuery without writing SQL.

My path into AI isn't a pivot. It's a progression. I built ML pipelines at American Express, completed a Udacity Deep Learning Nanodegree covering CNNs, RNNs, and GANs, and hold an MS in Computer Science from Arizona State (GPA 3.7) with coursework in data mining and distributed systems. The last two years at Walmart have been spent integrating LLMs and predictive models directly into production infrastructure.

I'm targeting roles where strong systems thinking meets applied AI — teams building LLM platforms, AI-native products, or agent infrastructure where production engineering depth and AI implementation both matter.

MS

Computer Science

Arizona State University · GPA 3.7

BE

Computer Engineering

PICT, India · GPA 3.5

ND

Deep Learning Nanodegree

Udacity · CNNs · RNNs · GANs

Let's talk about building AI that ships.

If you're working on LLM platforms, agent infrastructure, or AI-native products and need production engineering depth — I'd like to connect.

Open to senior AI/ML engineering roles at cloud platforms and AI-first companies in the Bay Area.