Technology strategy and enterprise AI professional with 10+ years across consulting, corporate strategy, and transformation delivery. I help senior stakeholders make clearer decisions across AI use cases, architecture, governance, operating model, investment, and measurable business impact.
"I help leaders turn enterprise AI and technology strategy into governed systems, operating models, and measurable business value."
I work where technology strategy becomes a governed operating model that executives can trust. Across HCLTech, Genpact, Deloitte, 7-Eleven, and other roles, I have led and shaped work across enterprise AI, platform modernization, cost transformation, customer experience, and operating model change. The common thread has been turning complex technology priorities into clearer decisions, accountable delivery systems, and measurable business outcomes.
My edge is the combination of strategy judgment and execution discipline. I have worked across consulting delivery, corporate strategy, client-side transformation, and entrepreneurial environments, which has shaped a practical view of what creates executive trust: clear economics, transparent governance, practical tradeoffs, accountable owners, and delivery rhythms that surface risk before it becomes noise.
I bring that perspective to enterprise AI and technology transformation work. I help senior stakeholders move from ambition to decision clarity: which use cases to fund, what architecture and controls are required, how delivery should be governed, where value will come from, and what operating model is needed to scale. In 2025, I completed my MBA at UT Austin McCombs with a focus on AI and Quantitative Methods, strengthening the analytical foundation behind more than a decade of technology, transformation, and delivery leadership.
I work at the point where technology strategy has to become a funded roadmap, a governed delivery model, and a measurable business outcome.
I help leaders clarify where AI, cloud, data, automation, and platform modernization should be used, what tradeoffs matter, and what must be true before committing funding, architecture, or delivery capacity.
I build operating rhythms that make executive decisions easier: KPI models, RAID discipline, decision logs, release gates, value tracking, and governance forums that connect technical work to business accountability.
I translate between executives, product owners, engineers, data teams, finance partners, vendors, and delivery teams so complex technology programs can move with clarity, control, and shared accountability.
A consistent pattern across the work: ambiguous executive mandate, technology and operating model complexity, cross functional execution, and outcomes senior leaders could use to make decisions.
A Fortune 100 financial services client needed to move GenAI, contact center AI, and automation work from scattered initiatives into a more governed portfolio across finance and technology functions.
Built KPI based portfolio governance across six workstreams, led a 12 person GenAI and Google Cloud CCAI team across 15+ finance and technology processes, and shaped two strategic transformation pursuits with client leadership.
Enabled $4MM+ labor cost avoidance, 60% manual effort reduction, and 40% faster reporting cycles while scaling the delivery organization 4.5x in five months and giving leaders a clearer operating view of value, capacity, and execution risk.
Executive leadership had paused a $139MM Food and Beverage Modernization Program with roughly 7,800 stores in scope and needed a clearer view of committed spend, restart economics, delivery scenarios, and execution exposure.
Rebuilt the program economics, restart scenarios, delivery timeline, and committed spend view, while supporting Project Green, a $500MM cost optimization initiative, alongside McKinsey consultants using WAVE.
Surfaced $52MM in noncancelable purchase orders that leadership did not have full visibility into, informing the go or no go decision, strengthening the restart case, and clarifying the financial exposure behind the modernization roadmap.
A global wealth manager needed to improve advisor access to institutional knowledge, modernize a portfolio risk platform, and raise delivery maturity across a large distributed engineering organization.
Directed delivery of a GenAI knowledge platform using LLM, RAG, and agentic workflow patterns, led modernization of a third party integrated portfolio risk platform, and coached 15+ Scrum teams while managing engagement governance and commercial operations.
Supported a platform serving 17,000+ professionals, improved latency by 12%, and raised sprint predictability by 30% and delivery velocity by 25% on a $3.8MM+ annual engagement.
A leading US telecom provider needed AI driven forecasting to guide a $24MM promotional budget and a parallel modernization of a national IVR platform touching retail customers at scale.
Served as Release Train Engineer across a 21 member ART spanning data science, engineering, and business teams, led PI planning and model delivery governance, and coordinated a 26 member team for the IVR modernization program.
Forecasting supported $360MM in Q4 business impact, while the IVR platform reached 1,252 stores and 142.8MM+ customers, with customer satisfaction up 20%, wait times down 27%, and 100% billing realization on a $5.7MM engagement.
I built a working portfolio of enterprise AI artifacts to show how technology strategy becomes decision architecture. Each artifact makes a critical AI leadership question visible: which use case to fund, whether the data is ready, how model quality is evaluated, what deployment evidence is required, how governance decisions are made, how value is measured, and how the system is operated after launch.
A working portfolio of enterprise AI artifacts, organized around the decisions that shape technology strategy, delivery governance, financial impact, and operating models. Each artifact turns a complex enterprise challenge into a structured view of value, risk, ownership, feasibility, and execution readiness.
I combine strategy framing, executive communication, delivery governance, and technical fluency so AI and modernization programs can move from ambition to funded roadmap, governed execution, and measurable impact.