Driving AI solution and execution at enterprise scale.
As Senior Manager of Data Science at Lowe’s, I direct the roadmap and deployment of advanced ML, Generative, and Agentic AI to transform complex retail operations and deliver measurable business value.
About
About me
I transform complex data science and AI into enterprise-ready products.
With over 19 years in data science and AI, my expertise spans from traditional machine learning and MLOps to orchestrating modern, autonomous AI frameworks. My foundation was built on large-scale analytics ecosystems like Hadoop and Spark, which evolved into a deep focus on the underlying architecture: designing enterprise data platforms and the intelligent data products they power.
Building on this foundation, my current work focuses on driving the AI/ML strategy and execution across store operations, store inventory management, and asset protection to deliver measurable business outcomes.
- Author of Breaking Into AI
- Published researcher on applied AI
- M.Tech, Data Science & Engineering, BITS Pilani
Core expertise
Also work with
What I do
Areas of expertise
AI Strategy & Team Leadership
Directing high-performing data science teams, defining enterprise AI/ML roadmaps, and bridging the gap between complex technical architecture and strategic business outcomes.
Generative & Agentic Ecosystems
Orchestrating autonomous execution loops, Text-to-SQL validation frameworks, and LLM-as-a-Judge quality systems to power intelligent enterprise applications.
Enterprise MLOps & Production AI
Scaling machine learning lifecycles and resilient model deployment strategies across enterprise platforms, leveraging Vertex AI, Kubeflow, and MLflow.
Retail Analytics & Business Intelligence
Delivering metadata-driven business intelligence, advanced forecasting, and automated insights that drive store-controllable KPIs and asset protection.
Scalable Data Architecture
Designing robust streaming and batch processing ecosystems utilizing modern lakehouse and data-mesh paradigms to power decision-ready products.
Cloud Infrastructure Strategy
Architecting distributed, highly available, and cost-optimized data processing infrastructures across GCP, Azure, and Databricks.
Selected work
Work that shipped
AI-Powered Space Optimization
Directed the architecture of a machine-learning engine that optimizes product placement and shelf-space utilization across a national retail fleet. I orchestrated a heavily parallelized, distributed compute pipeline that unlocked enterprise-scale optimization, directly improving space utilization and sales performance. Backed by published research.
Read the paper →Conversational Analytics Agent
Architected a Generative AI agent powered by advanced Text-to-SQL validation frameworks, enabling business leaders to query enterprise data warehouses in natural language. It democratized data access, turning complex metadata into instant, actionable insights for non-technical teams.
GenAI Quality Platform
Championed and deployed a unified AI quality platform built on an LLM-as-a-Judge framework. The automated system proactively surfaces quality and reliability issues, ensuring safety and compliance across production Generative AI applications.
AI-Driven Replenishment
Scaled predictive machine-learning models that intelligently prioritize shelf replenishment. The initiative replaced manual, scan-based methods with automated forecasting, streamlining complex operational workflows across a large-scale retail footprint.
Real-Time Store Performance Platform
Led the development of a 360° store-performance platform powered by real-time POS streaming, establishing a single source of truth for store-controllable KPIs and driving data-informed operational decisions across the retail fleet.
Career
My journey
Experience
Education
Author
My book
Breaking Into AI Breaking Into AI
The Complete Roadmap to Becoming an AI Engineer from Scratch: LLMs, Agents, RAG, and a 90-Day Action Plan for Software and Data Engineers.
A practical, no-fluff roadmap for software and data engineers who want to become AI engineers. It covers LLMs, agents, RAG, and a concrete 90-day action plan drawn from nearly two decades on the front line of every major platform shift.
View on Amazon →Research
Publications
View full profile on Google Scholar →
Blog
Latest writing
A field guide to the leading agentic AI frameworks in 2026, LangGraph, Google ADK, Claude Agent SDK, OpenAI Agents SDK, CrewAI, Pydantic AI, and Microsoft Agent Framework, and where each one fits.
Why I started writingA home for my notes on AI, data, and building teams that ship.
Notes from GTC and Cloud Next: we have stopped talking about just modelsReflections from NVIDIA GTC and Google Cloud Next 2026 on the shift from AI models to AI systems that hold up in production.
Get in touch
Let's connect
Always glad to exchange ideas on AI, data, and building teams - or to talk through an interesting problem. Find me on LinkedIn.
Connect on LinkedIn →