Connecting the dots between architecture, engineering, and commercial outcome.
Broad, hands-on experience building high-scale platforms across global enterprises — specialized in one thing: turning ambiguous business problems into clean, resilient architectural decisions that teams can execute and organizations can rely on.
I operate at the intersection of engineering leadership, cloud-native modernization, and increasingly, Generative AI — building the kind of infrastructure that doesn't just handle today's load, but is ready for tomorrow's unknowns.
From architecture review gates to multi-million dollar RFP wins — I operate at the engineering/business boundary. Platform decisions, P&L ownership, and cross-functional delivery at enterprise scale.
Production systems across cloud-native platforms, real-time data pipelines, and AI/LLM deployments — not prototypes. All of it proven under enterprise load and compliance constraints.
Every technical tradeoff carries a cost — in delivery risk, operational overhead, or time-to-market. I translate architecture into commercial outcomes that engineering leaders, product owners, and C-suite sponsors can align on. Presales, RFPs, and advisory engagements have made this muscle second nature.
Enterprise platforms serving millions of users across global markets don't survive retrofits. From Hitachi's EAM suite to financial platforms processing millions of transactions, distributed resilience, event-driven design, and data contracts aren't premature optimisation — they're survival.
The ROI of GenAI isn't in demos. It's in measurable toil reduction: faster documentation, intelligent triage, agentic orchestration of repetitive workflows. I treat LLM integration the same way I treat cloud adoption — ruthlessly tied to process outcomes and productivity gains.
Advisory that ends at the slide deck doesn't count. I stay hands-on through delivery — owning architecture reviews, code-level decision gates, and cross-team alignment — because enterprise software fails more often in execution than in design.
I've driven multi-million dollar savings not by cutting corners, but by right-sizing infrastructure, eliminating redundant integrations, and building systems that operations teams can maintain. P&L accountability has shaped how I design from day one.
A solution engineers respect but executives won't fund, or that clients approve but delivery teams can't execute, isn't a solution — it's a proposal. A versatile career across presales, consulting, and delivery has taught me that architecture fluency means speaking Java, Spark, and boardroom in the same breath.
Challenge: Global energy utilities needed to move from reactive to predictive asset management — monitoring thousands of critical assets across distributed power grids and industrial infrastructure.
What I built: Led Platform & Data Engineering tracks for the Hitachi Lumada EAM/APM suite. Designed microservices for data ingestion, health-check monitoring, and reliability modeling. Built Azure + Databricks + Spark pipelines processing terabytes of industrial sensor data per hour.
Challenge: A leading Japanese industrial conglomerate needed a digital platform to manage building operations, energy consumption, and occupant wellbeing across mission-critical facilities.
What I built: Engineering leadership for BuilMirai (HMAX for Building) — a Lumada-based digital service connecting frontline workers, building systems, and energy data streams. Contributed to architecture decisions for data pipelines and operational dashboards.
Challenge: A leading diversified industrial manufacturer needed a unified IoT platform to remotely monitor equipment and enable predictive maintenance across globally distributed field assets.
What I built: Led a 12-member team to design and deliver PRISM — an Angular + .NET platform ingesting real-time telemetry from LTE-M IoT devices. Owned full architecture: data capture pipeline, REST API layer, release automation, and quality framework.
Challenge: American Express needed to launch its first-ever Gift Card product in India while scaling a B2B virtual payment platform across UK, Canada, and global markets.
What I built: Tech Lead and integration architect — designing API contracts, virtual account workflows, transaction verification logic, and real-time + batch reconciliation pipelines. Coordinated cross-functional teams across geographies.
Built to close the gaps I kept hitting — in architecture governance, presales qualification, and platform engineering. All open source, all free.
LLMs produce generic architecture output with no awareness of enterprise constraints. archpilot fixes that: 50+ rule files and personas give any LLM the context to produce consistent, reviewable decisions. The CLI scaffolds ADRs, C4 narratives, and cross-cutting concern docs from your terminal in minutes. The GitHub Action scores every PR 0–100 against those standards automatically — governance without the ceremony.
Technical sellers over-invest in deals they can't win. cadex is a browser-based qualification framework that scores risk across architecture complexity, delivery confidence, and commercial dimensions — before a single slide is built. Use it to decide where to invest solutioning effort and when to walk away. Built from real presales patterns across enterprise IT engagements.
There's no manual for solutions architects navigating enterprise deals. This open playbook covers discovery frameworks, architecture defence patterns, stakeholder communication scripts, and how to run a technical win — not just respond to an RFP. Everything needed to own the deal, not just support it. cadex qualifies the opportunity; this playbook wins it.
Industrial IoT platforms at scale share the same hard problems: edge reliability, telemetry volume, digital twin synchronisation, multi-tenant security. This 24-section reference covers 100K+ concurrent asset deployments — from field PLCs to cloud analytics — with real architectural decisions, not whiteboard diagrams. Skip the 6-month architecture phase; the hard choices are already here.