Work

Programs organized by the problem, not the service.

Client engagements are described in generalized form. The domains below reflect where I've spent the last eighteen years across global banking, asset management, and enterprise SaaS, grouped by problem, approach, and outcome. Named references available on request.

01 · Domain

Financial Services Platforms

Global banking · Regulatory reporting · Asset management

The problem: Regulated financial platforms have to be correct, auditable, and safe to change inside compliance cycles that don't move.
The approach: Integrity, traceability, and controlled change designed in from day one. Not compliance controls bolted on later.
The outcome: Platforms that survive their own audits, year after year. Change that never breaks the trail behind it.

02 · Domain

Cloud & Platform Engineering

Enterprise financial services · Hospitality · SaaS · Internal platforms

The problem: Cloud gets treated as a hosting decision. What the business actually inherits is a new way to work, or a new way not to.
The approach: Azure environments built as compounding capabilities: landing zone, identity, standards, and developer experience. In a migration, the business inherits a capability, not just a bill.
The outcome: Cloud that keeps paying back. Migrations that end with something the business can actually run.

03 · Domain

Enterprise Architecture

Enterprise SaaS · Financial platforms · Regulated environments

The problem: Enterprise systems lose coherence as they scale. Not from bad decisions, but from delivery pressure and drift.
The approach: Set direction across domains, integration, data flow, and non-functional standards. Draw boundaries that survive reorganizations.
The outcome: Systems that stay coherent, and safe to change, once the people who built them have moved on.

04 · Domain

SaaS Product Engineering

Enterprise SaaS · Governance, risk & compliance · Multi-tenant platforms

The problem: Enterprise SaaS products get complicated fast. Early architectural decisions quietly determine what is possible five years later.
The approach: Own the product end to end. Domain modeling, tenancy, and integration as structural decisions on day one.
The outcome: Products that scale in complexity without losing coherence. ClearGRC, built on this pattern, is an AI-assisted governance platform supporting 35+ compliance frameworks. Compliance as a byproduct of the work, not a parallel spreadsheet.

05 · Domain

Applied AI in Enterprise

Enterprise · Regulated environments · Financial services

The problem: Pilots prove capability. Production AI has to be trustworthy, evaluable, cost-aware, and something a real team is willing to be on the hook for.
The approach: Design AI as an end-to-end system. Retrieval, evaluation, oversight, cost, and workflow integration treated as first-class from the start.
The outcome: AI systems that still make sense on a Monday morning, six months in. The kind the business quietly relies on.

06 · Domain

Engineering Leadership

Distributed engineering teams · Enterprise SaaS

The problem: Delivery speed is easy to measure. Long-term ownership isn't. Organizations pay for the difference later.
The approach: Align architecture, teams, and standards around what matters after go-live. Emphasis on ownership, governance, and mentorship.
The outcome: Engineering organizations that ship quickly, and still recognize their own systems in year three.

07 · Domain

Data Platforms & Integration

Financial services · Enterprise data · Regulated environments

The problem: Enterprise data platforms carry more of the business than most architectures admit. And inherit every constraint the business does.
The approach: Security, provenance, and controlled change built in from the beginning. Data-handling patterns designed to hold under audit.
The outcome: Data platforms that stay honest under scale, audit, and organizational change.

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