I make enterprise AI actually work
I turn frontier models into production enterprise systems — designing the architecture, governance, and adoption that make AI deliver at organizational scale.
Enterprise AI Systems Leader • Former Venture CTO • Princeton + Cornell Tech
Enterprise AI delivery across industries
Previous work includes teams at BCG, American Express, Palantir, National Grid, AIG, Pumpkin, and Nexa.
- BCG
- American Express
- Palantir
- National Grid
- AIG
- Pumpkin
- Nexa
Brought in when AI initiatives are high-stakes, cross-functional, and need to move from model to operating system.
Enterprise AI deployment patterns
Repeatable patterns for embedding AI into real enterprise systems — across industries, regulatory environments, and organizational complexity.
AIG: AI-assisted underwriting & claims at enterprise scale
Designed and delivered production GenAI systems embedded into underwriting and claims workflows — built for adoption, governance, and measurable operational impact in a regulated enterprise.
Role: Technical lead (BCG) — architecture, delivery leadership, stakeholder alignment
Impact: Reduced cycle times, increased throughput, scaled AI assistance across major business workflows.
Read case studyEnterprise platform modernizationAmerican Express: Business Checking platform delivery
Led engineering and product execution for a customer-facing fintech platform — balancing speed-to-market with reliability, security, and long-term architectural durability.
Role: Engineering & Product Lead — architecture direction, delivery execution, cross-team coordination
Impact: Shipped customer-facing platform with durable foundations for scaling and team ownership.
Read case studyProduct + platform transformationNational Grid: Cloud & digital transformation leadership
Led technology direction across cloud modernization and internal product delivery during a large-scale digital transformation — without destabilizing critical utility operations.
Role: Senior technology leader — platform strategy, execution leadership, stakeholder alignment
Impact: Improved platform maturity, delivery velocity, and operational reliability across the transformation.
Read case studyWhat I do
I lead enterprise AI from strategy through production. The work spans architecture, governance, workflow design, and organizational adoption — because shipping a model is not the same as shipping an AI system.
AI systems architecture
Designing production AI platforms that integrate frontier models with enterprise data, security, and infrastructure at scale.
Enterprise workflow transformation
Embedding AI into core business workflows where it changes how work actually gets done — not just how it gets demoed.
Governance, risk & trust
Building governance, evaluation, and risk frameworks into AI systems from day one — so they ship in regulated environments.
Adoption & operating model design
Designing the organizational change, training, and feedback loops that turn deployed AI into adopted AI.
Cross-functional executive leadership
Aligning engineering, product, legal, compliance, and business leadership around shared AI outcomes and delivery milestones.
Production delivery at scale
Owning end-to-end execution from architecture through rollout — across multi-quarter, multi-team enterprise programs.
How I think about enterprise AI
Enterprise AI fails when teams treat it as a technology problem. It succeeds when they treat it as a systems problem.
Models are infrastructure, not product
Frontier models are a starting point. The real work is the system around them — data pipelines, evaluation, UX, and integration with how the business actually operates.
Workflow design is the multiplier
AI that sits outside core workflows gets ignored. AI embedded into how people already work changes throughput, quality, and decision speed.
Governance is a product feature
Trust, compliance, and risk management aren't obstacles to deployment — they're requirements for it. Build them in from day one or rebuild later.
Adoption is an operating model problem
Technical deployment without organizational change produces shelfware. Successful enterprise AI rewires roles, incentives, and feedback loops.
Enterprise AI is organizational, not just technical
The hardest problems aren't model performance — they're cross-functional alignment, change management, and sustained executive commitment.
Experience
2023 — 2025
Principal AI Engineer & Enterprise AI Lead
BCG X
Led enterprise AI systems delivery for Fortune 500 clients — owning architecture, governance design, and production deployment of GenAI across regulated workflows.
Key outcomes
- Architected and delivered production AI systems with enterprise governance and evaluation frameworks.
- Designed AI-augmented workflows that drove measurable adoption and operational impact.
- Led cross-functional alignment across engineering, product, compliance, and executive stakeholders.
2021 — 2023
Venture CTO
BCG Digital Ventures
Served as CTO across enterprise transformation engagements — leading technology strategy, platform architecture, and operating model design for large-scale digital initiatives.
Key outcomes
- Directed enterprise solution architecture across cloud, IoT, and platform modernization programs.
- Designed delivery and ownership models for sustained post-engagement execution.
- Led execution in high-visibility, multi-stakeholder enterprise environments.
2020 — 2021
Engineering & Product Lead
Amex Business Checking (via BCG)
Led engineering and product execution for a customer-facing fintech platform — balancing rapid delivery with architectural durability and organizational handoff.
Key outcomes
- Shipped platform capabilities with reliability-first architecture tradeoffs.
- Established operating model for long-term team ownership and scaling.
- Drove cross-team coordination across product, engineering, and compliance.
2019 — 2020
Feature Team Lead
Pumpkin / Zoetis (via BCG)
Led product engineering for a venture-stage pet health insurance platform — building architecture foundations and recruiting the team for durable ownership.
Key outcomes
- Delivered core customer-facing product features from zero to production.
- Established scalable front-end architecture patterns.
- Recruited and transitioned engineering for sustained post-venture ownership.
Pre-2019
Prior Roles
Harman, TouchCare, Windsor Circle, Epic Systems
Built systems integration and platform engineering experience across healthcare, martech, and consumer electronics — developing the cross-domain foundation for enterprise systems work.
Key outcomes
- Delivered across healthcare IT, marketing platforms, AR systems, and consumer electronics.
- Built depth in systems integration, platform architecture, and cross-domain engineering.
Education
Cornell Tech / Technion — M.S. Information Systems & M.S. Applied Information Science (Cum Laude)
Princeton University — B.S.E. Operations Research & Financial Engineering
Hack Reactor — Advanced Software Engineering Immersive
Let's talk enterprise AI
If you're an enterprise leader deploying AI at scale, a frontier AI company building for enterprise adoption, or a product and technology executive navigating high-stakes AI systems — I'd welcome the conversation.
I'm always interested in comparing notes with people building enterprise AI that actually ships, scales, and earns trust.