Engineering Leadership · Amazon · AI Product Experiences

Building AI product experiences, scalable systems, and the technical foundations behind them.

I work at the intersection of engineering depth, product thinking, and execution. My experience spans AI-powered customer experiences, agentic and tool-driven systems, search and language products, public-sector platforms, commerce systems, and large-scale production environments. I care about turning emerging capabilities into reliable product behavior that creates real customer value.

AI Product Experiences Agentic Systems Distributed Systems Multimodal Interfaces Developer Tools Technical Leadership Cross-Domain Product Thinking
Selected Impact
01 / PRODUCT

AI Product Experiences at Amazon

Worked on Rufus experiences across search, detail, homepage, and cart surfaces, including inline and conversational experiences that connect user intent to helpful actions.

02 / SCALE

Production AI at Scale

Built for high-scale production environments where reliability, latency, and customer trust matter deeply. Recent work includes customer-facing AI experiences on major commerce surfaces operating under real performance constraints.

03 / SYSTEMS

Agents, Tools & Multimodal Systems

Designed and shipped agentic and tool-driven experiences, including comparison flows and multimodal capabilities, with a focus on making AI useful inside real product behavior rather than isolated demos.

Leadership & Community
01 / INNOVATION

Hackathons & Prototyping

Won multiple Amazon internal hackathons, including global competitions, and helped organize hackathons that accelerated experimentation, prototyping, and practical delivery.

02 / LEADERSHIP

Cross-Functional AI Enablement

Helping teams adapt to the newest shifts in AI by connecting product, design, and engineering with more effective ways of building, validating ideas, and working together.

03 / BAR RAISING

Raising the Technical Bar

Focused on strong engineering judgment, quality, and long-term thinking, including helping other builders navigate ambiguous problems and turn promising ideas into durable execution.

Perspective
01 / THESIS

AI as a System Verifier

The real leverage of AI is not only faster output. It is closing the loop. Agents that observe, test, fail, fix, and verify their own work reduce human review load instead of simply shifting it upstream.

02 / SYSTEMS

Reducing the Alignment Tax

As code generation becomes cheaper, the bigger bottleneck becomes alignment across systems, teams, and constraints. Making those constraints machine-readable feels like the next important architectural step.

03 / COLLABORATION

Breaking Translation Layers

One of the biggest organizational effects of AI is reducing the translation tax between product, design, and engineering. Teams that build together in real time can move with much more clarity and speed.

How I Work
Approach &
Principles

I care about raising the bar technically, organizationally, and in how strong engineering judgment is developed. That means building robust systems, recognizing patterns across domains, creating clarity in ambiguous spaces, helping teams adopt better ways of working, and using AI not as a shortcut for output alone, but as a way to improve verification, collaboration, and execution quality.

Build for real users Make AI practical Reduce translation tax Raise the technical bar Turn ambiguity into systems Connect patterns across domains Enable other builders
Selected Background
Work
History
2015 - Now

Amazon

Senior Software Development Engineer

Building high-impact software systems and customer experiences at scale, with recent focus on AI-powered product experiences, agentic workflows, multimodal interfaces, and technical leadership across customer-facing commerce surfaces. Earlier Amazon work included Alexa Shopping, international launches, authentication, peak readiness, and commerce platform initiatives.

Prior

Tureng

Builder & Product Creator

Built Tureng, a widely used multilingual dictionary and language product, reflecting a long-term focus on usefulness, search relevance, product quality, and durable execution across a real consumer product.

Foundation

Earlier Roles

Engineering, Product & Teaching

Background spanning software engineering, project leadership, public-sector platforms, search systems, instruction, and product building across different organizational environments and scales, creating a broad base for connecting ideas across domains.

// Contact

Technical depth, product instinct, and a builder mindset.

Open to thoughtful conversations around AI product development, engineering leadership, and practical applications of agentic systems.