Own the end-to-end technical design for a cloud-agnostic engineering platform with AI-assisted capabilities, aligned to a regulated environment control and DDD domain segregation. You''ll set the reference architecture, guide build decisions, and ensure the solution is operable, secure, and auditable. What success looks like (outcomes) A clear target architecture that teams can implement without interpretation gaps. DDD-aligned boundaries: domains are separated, ownership is clear, and integration is deliberate. Tooling choices are justified and consistent with governance (SCM/CI/IaC/GitOps/IDP). AI capability is introduced safely: scoped permissions, traceability, and human approvals. Key responsibilities Define the platform reference architecture (cloud-agnostic) covering: SCM/CI strategy (GitHub vs Bitbucket and implications) IaC approach (Terraform/OpenTofu vs Pulumi usage guidelines) Kubernetes baseline (multi-cluster, tenancy, networking, secrets) GitOps with ArgoCD and promotion strategies Container registry strategy and governance IDP approach (Backstage/Compass) and operating model Drive DDD adoption: Domain boundaries, context maps, ownership model, and anti-corruption layers where needed Define non-functional requirements and controls: Security, resilience, observability, change management, audit evidence, SDLC controls Establish architecture governance: Decision records, architecture reviews, standards, and cross-team alignment Align stakeholders ac