Skip to main content

Enterprise Cloud & AI Platform Leader

Shafiq sets the cloud and AI platform direction an engineering organization builds on — turning fragmented infrastructure into governed, self-service leverage, and aligning that platform with what the business is actually trying to ship.

Staff Platform Architect and enterprise platform leader who operates on two planes at once: the technical plane — enterprise cloud architecture, application hosting, API management, and the AI control plane that every product team depends on — and the strategic plane, where platform investment gets translated into business outcomes, funded, and aligned across teams and leadership. The throughline is leverage: standardize the hard parts, expose the right primitives, keep security and cost as design inputs rather than afterthoughts, and make the platform a product that engineers actually want to build on. He is the rare architect who is fluent in both the deep technical trade-off and the executive conversation that decides whether it happens.

Follow the profile

Ask the AI assistant — instant answers grounded in this profile

70k+

infrastructure resources migrated and modernized without losing delivery speed

700+

services kept shipping through a platform-wide re-platforming

1B+

monthly API gateway requests architected and operated at scale

200+

Azure subscriptions hardened through hub-and-spoke zero-trust networking

Portfolio

Three platform systems the rest of the org now builds on — a governed AI control plane, a 70k-resource migration run without losing a day of delivery, and a zero-trust bootstrap that turns acquisitions into onboarded teams.

  • 70k+ resources migrated from Terraform Cloud to Scalr with zero delivery interruption
  • 700+ services preserved with uninterrupted deployment velocity through the migration
  • 2+ internal agentic applications powered safely by the governed AI control plane
  • 1B+ monthly requests served through enterprise API gateway architecture
See career timeline & case studies

Playbook

The operating model favors clear boundaries, replayable decisions, and automation with receipts — and knows a platform only matters if the org can be brought along with it.

Bound autonomy before you optimize execution speed — safety is a design input, not a later pass
Standardize the substrate so teams can differentiate at the product layer — leverage over heroics
Full approach & philosophy