Principal Enterprise Architecture

About the Role

Building a comprehensive set of enterprise architecture and engineering standards — researched, written, validated, and published as both a governance reference and a learning resource for architects, engineers, developers, and product teams across the organization.This is standards authorship, grounded in real, practiced experience across the full breadth of modern enterprise architecture — the ability to explain not just what the rule is, but why it exists, and to teach it clearly to a mixed technical audience.

Responsibilities

Building a comprehensive set of enterprise architecture and engineering standards — researched, written, validated, and published as both a governance reference and a learning resource for architects, engineers, developers, and product teams across the organization.This is standards authorship, grounded in real, practiced experience across the full breadth of modern enterprise architecture — the ability to explain not just what the rule is, but why it exists, and to teach it clearly to a mixed technical audience.Author complete, publication-ready standards spanning the full enterprise architecture landscape, organized across five domain clusters:

Software & Application Architecture

Application Architecture — microservices, modular monolith, and event-driven styles; domain-driven design and service boundaries; build, buy, and SaaS decision considerations; COTS configuration versus customization; modularity, coupling, cohesion, and maintainabilityFront-End & User Experience — web and mobile framework selection criteria, native/hybrid/responsive approaches; design systems and reusable component libraries; accessibility requirements including WCAG; performance budgets; micro-frontend use criteria and governanceDevelopment Standards — language-specific coding expectations; code review and scanning requirements, including AI-assisted vulnerability checking; source code and architecture documentation; open-source usage and dependency management; inner source practices; repository organization and code ownership

Integration, Delivery & Operations

API & Integration Practices — REST and GraphQL conventions, resource/endpoint design, versioning and compatibility; standard error handling; event streaming patterns, schemas, and versioning; canonical data models; contract testing for APIs and events; integration observability and traceability (integration practices, not middleware products)Quality & Testing — test strategy and the test pyramid; unit, component, integration, contract, system, and end-to-end testing; test automation; performance and load testing; security testing alignment; quality gates and release-readiness evidenceCI/CD — branching strategies; environment strategy and promotion; pipeline expectations and reusable patterns; artifact versioning; deployment patterns including rolling, blue/green, and canary; feature flag lifecycle; release traceability, rollback, and software supply chain controlsObservability — application and integration logging, correlation, and retention; metrics and health indicators; distributed tracing; dashboards and alert readiness; minimum observability requirements before production releaseAdvanced Observability & Operations — service-level indicators and objectives, incident management, runbooks, operational readiness, and AIOps considerations

Security, Risk & Compliance

Security Architecture — identity and access management; SSO, MFA, privileged access, and least privilege; zero trust principles; encryption, key, and secrets management; SAST, DAST, dependency scanning, and SBOM expectations; threat modeling; third-party and software supply chain riskCompliance, Privacy & Risk — regulatory alignment, audit logging, records management, privacy by design, control traceability, and evidence expectations

Data & Platform Architecture

Data Architecture — data modeling, database selection, master and reference data, data quality, metadata, lineage, classification, retention, archival, data products, and warehouse or lakehouse guidanceInfrastructure & Cloud — hybrid and multi-cloud principles, landing zones, compute patterns, containers, serverless, Kubernetes, storage tiers, networking, infrastructure as code, tagging, and platform guardrailsResilience & Continuity — availability tiers, recovery time and recovery point objectives, backup and recovery, disaster recovery validation, fault tolerance, and resilience testing

Enterprise Applications & AI

Enterprise & Back-Office Applications — ERP, CRM, HCM, finance, asset management, work management, document and content management, workflow and BPM, low-code, and RPA platformsAI Skills Development — design of reusable AI agent “skills” for platforms such as Claude and comparable enterprise AI assistants: structure, instructions, inputs/outputs, authoring and documentation conventions, testing and validation, versioning and lifecycle, security and data handling, human review and approval, and platform-neutral guidance

Every standard follows the required structure:

Standard statementRationaleConcepts & teaching backgroundPractical guidanceApproved patterns & anti-patternsWorked examplesCompliance & validationExceptionsReferencesOwnership & review cycle.

Qualifications

12+ years as a Principal or Staff-level enterprise architect, solution architect, data architect, cloud/infrastructure architect, or enterprise applications architect — a genuine hands-on practitioner, not a documentation generalistDemonstrated experience authoring enterprise architecture or engineering standards, reference architectures, or governance documentation at scaleReal, hands-on depth in at least two or three of the five domain clusters above, as part of a small, named delivery team — breadth of awareness across all five is valued, but deep expertise is expected in a focused