STEM MBA candidate and Fisher Leadership Fellow with 9.5+ years driving corporate strategy and AI product management across Amazon, Oracle, KLA, Rakuten, Cisco & Microsoft. I secure VP-level buy-in, architect multi-quarter roadmaps, and translate frontier machine learning into scalable, multi-million dollar enterprise P&L growth.
I lead at the seam where deep technology meets business strategy. Over 9.5+ years, I've moved from building the models to defining the capital roadmaps that fund them — authoring 45 business cases that secured VP-level approval for 12 strategic initiatives across Amazon's Retail, Devices, Prime Video and AWS organizations.
My work is measured in outcomes the C-suite cares about: a $28M revenue impact for Kindle, a $20M ARR portfolio at Oracle, a 44% CTR lift at Amazon Ads, a 3× reduction in OpEx for 70M customers, and go-to-market cycles shortened by 25% through rigorous Lean Six Sigma process optimization.
Equally, I build the teams that deliver it. I've mentored 51+ engineers, spearheaded autonomous multi-agent pipelines (AURORA), and set the AI product vision for entire enterprise organizations. My STEM MBA at Ohio State's Fisher College formalizes the finance, operational strategy, and product-management craft behind that instinct.
"Translate technical complexity into actionable business plans — then build the cross-functional team that ships them."
— Operating Principle
Targeted credentials highlighting specific strategic leverage, technical architecture depth, and quantifiable business outcomes across distinct leadership mandates. All links provide instant, inline PDF access.
Positions deep technical competencies as strategic leverage. Emphasizes structured problem-solving, digital transformation roadmaps, business case approvals, and enterprise P&L outcomes.
Frames leadership around zero-to-one product lifecycles, user experience optimization, engineering prioritization, feature backlog management, and technical MLOps platform strategy.
Highlights deep applied science mastery: frontier LLMs, autonomous multi-agent orchestration (AURORA), GraphRAG, distributed GPU infra scaling, and proprietary model architectures.
Applies Lean Six Sigma (DMAIC), root-cause analysis (RCA), and AI automation to complex operational bottlenecks, digital inventory supply chains, and enterprise throughput scaling.
Concentrates on capital structure optimization, DCF/LBO modeling, treasury workflow automation, and algorithmic risk mitigation models for high-volume transaction ecosystems.
How I structure ambiguous enterprise problems into scalable, operational realities bridging tech and high-level strategy.
The structured "working backwards" mechanism I utilized to author 45 business cases, securing VP-level funding for 12 strategic initiatives across Amazon Retail, AWS, and Prime Video.
The technical blueprint behind the AURORA 10-agent pipeline. Defines state-graph routing, asynchronous self-correcting verification loops, and O(1) label-based RBAC graph security.
An end-to-end DMAIC cycle and SIPOC playbook used to eliminate catalog mapping latency. Integrated Root Cause Analysis (RCA) directly into cloud infrastructure optimization.
A comprehensive strategy deploying generative AI workflows within financial operations to automate intent classification and function calling for global customer queries.
The rollout strategy for the 'Rec-Rainbow' LLM engine. Mapped client segmentation, robust A/B testing infrastructure, and sequential monetization models across ad networks.
A comprehensive playbook for upskilling global organizations. Detailed the deployment of 29 reusable Claude Code skills, CI/CD pipeline heuristics, and internal engineering hackathons.
Authored 45 comprehensive PR/FAQs, successfully securing VP-level approval and funding for 12 strategic AI initiatives shaping Digital Acceleration across 4 organizations.
Launched "HELIUM-PRISM," a patented multi-modal model accelerating product mapping. Outperformed legacy baseline systems with 9X lower latency and 14.5X better memory efficiency.
Led strategic demand-shaping action for the Kindle e-reader organization, enriching the digital product catalog to drive a 15% QoQ increase in unit sales and a 12% uplift in attach rates.
Managed product strategy and 8 agile sprints across 4 healthcare data verticals. Led the acquisition of 42 international enterprise clients by shipping 9 low-latency AI solutions.
Developed predictive analytics forecasting network equipment failures in real-time for Webex, preventing global service outages and improving system uptime availability by 78%.
Designed production-grade label-based RBAC protecting 1.5M+ nodes across 15 Neo4j Databases, reducing credential leak exposure by 92% at infinite scale (O(1) bitmap time).
Each role framed as it would be in a consulting case: the context, the numbers, and the precise execution I drove.
Led enterprise AI governance and autonomous workflows, building highly secure, scalable multi-agent ecosystems.
Set AI product strategy and led cross-functional execution across AWS, Amazon Pay, Kindle, Prime Video & Retail Science.
Owned product strategy and delivery for enterprise document-intelligence and healthcare-data verticals.
Bridging deep technical science with executive management, finance, and enterprise strategy.
Great strategy comes from uncovering the real challenge behind the stated one. I frame ambiguity into structured, testable hypotheses before committing resources or writing a single line of code.
Rational, evidence-based decision-making under uncertainty is the core of the craft. I pair quantitative rigor and financial modeling with the judgment to move decisively when the data points the way.
Mentoring 51+ engineers and running cross-functional recognition programs taught me that durable results come from teams that grow. I invest heavily in talent, continuous coaching, and a culture of path-breaking work.
I care about the long-term scalability of a solution and lasting organizational change. I design systems that lower infrastructure costs, increase capital efficiency, and deliver results that endure long after a project concludes.
Whether it's an AI product strategy, a rigorous go-to-market plan, or a multi-million dollar consulting engagement — I'd welcome the conversation.