I diagnose product problems that block revenue growth and operational scale, with 18+ years leading product strategy, product management, and UX strategy for content platforms and e-commerce systems.
San Francisco Bay Area
I owned Adobe Express’ end-to-end content pipeline workflows and internal tools with a mandate to scale content velocity. I delivered AI-driven business workflow enhancements, content quality and curation systems that reduced metadata errors, improved guideline compliance, and accelerated time-to-publish across Express’ contributor ecosystem.
Worked across engineering, content operations, design, and moderation teams spanning US and India. Shipped systems used by thousands of contributors submitting templates every week.
1. AI-Infused Submission Workflow
Devised a prompt-based auto-suggest which generated brand-compliant keyword suggestions at submission time; created the prompts, ran feasibility tests, and influenced leadership to adopt the approach. Implementation of this auto-suggest reduced submission errors by ~80% and compressed moderation timelines by ~50%.
Extended the same insight into Autometa, a RAG prototype that auto-fills all metadata fields using brand rules, enabling consistent quality at scale without adding moderation load demonstrating a scalable path for multiple Adobe brands
2. Template Quality Checker
Envisioned this content submission tool as a “Grammarly for visual creations”; developed competitive insights, utilized past UX research insights, scoped phased delivery, and prototyped prioritized quality checks Launched pilot in Q4 2024 with GA in Q3 2025, improving upstream submission quality and reducing moderation cycles.
3. Collection Curation Tool (Internal Ops)
Conducted discovery, mapped workflows, created prototypes for complex nested row patterns and validated feasibility with curators and partner teams. Tool shipped within 3 quarters, accelerating curation cycles without increasing headcount.
Strategic Impact
Improved core throughput drivers across submission, moderation, and curation, directly increasing overall content velocity, boosted downstream content discovery (e.g., search CTR ~2X)
San Francisco Bay Area
San Francisco Bay Area
I owned the SMB growth track for Adobe Stock, covering checkout, renewal, and retention levers. Within this charter, I delivered a marquee multi-asset engagement initiative that surfaced adjacent-category value and drove a 10X CTR lift and 61% growth in multi-asset downloads, significantly improving downstream retention. Partnered across GTM, product, engineering, and UX research teams.
1. Multi-Asset Engagement
I improved Adobe Stock’s video asset engagement for photo plan subscribers.
Diagnosed that customers ignored multi-asset value messaging because it appeared as an upsell in wrong moment;
Legacy UI surface allowed for a single messaging slot that customers skipped
I conducted product discovery and prototyped the value message as a next-best-action in underserved journey moments on surfaces where customers were already paying attention such as download confirmations
Shipped a reusable cross-category discovery pattern delivering the 10× CTR and 61% multi-asset download lift.
Impact
Shifted GTM and product toward behavior-based engagement and away from static awareness-only surfaces
Supported downstream revenue goals by enabling customers to realize more value from their subscriptions
Improved checkout clarity and upsell patterns across the SMB and retail tracks, providing a foundation that Adobe later extended to GenAI offerings in 2024
San Francisco Bay Area
I led multimodal shopping experiences for the Alexa Shopping organization with a mandate to validate whether Echo screen devices could serve as viable top-of-funnel shopping channels. I built research-backed shopping frameworks and launched smart-home and gifting shopping betas that reached ~2M MAU across the US, UK, and Germany.
Discovered and abstracted customer journey archetypes for high-traffic categories. Eg: Smart home devices = “I don’t understand how this fits my home or solves a need”, Gifting = “I need something great right now but don’t know what’s appropriate”, Appliances = “I need functional, technical certainty before I buy”
Built guided shopping forward experiences under constraint that conversational flows on Echo devices weren’t designed for deep product exploration.
Created voice prototypes with guided “Q&A-based” decision flows that spotlighted the exact information modality customers needed at the right step.
Drove ~2M MAU across US/UK/DE during beta and validated Echo screen devices as a promising top-of-funnel shopping channel.
Introduced the decision-archetype model (exploratory, urgency-driven, technical assurance) that now informs Amazon’s AI shopping workflows.
Q&A patterns developed in my pod became the building blocks for Rufus, Amazon’s current AI product advisor. Example:
Smart home → exploratory starter questions (“What do other customers say?”)
Gifting → constraint-based prompts (“Will it fit?”, “Is this good for a 10-year-old?”)
Appliances → ownership-oriented filters (“How often do I replace filters?”)
San Francisco Bay Area
I led product discovery and redesigned Qwil’s core experience to focus on a tightly defined bullseye audience, shifting the product from a broad early-pay tool serving fragmented audiences to a targeted value proposition aligned with real customer motivations. By simplifying key workflows, and redefining the product's target B2B user, I helped Qwill sharpen its strategic narrative which contributed directly to the company’s eventual acquisition. I worked directly with the CEO and CPO to align product decisions.
Education
2005 — 2007
Indiana University Bloomington
Masters
2005 — 2007
2001 — 2005
University of Mumbai
BE
2001 — 2005
Georgia Institute of Technology
naval public school