ROLE SUMMARY As Director, AI Architecture Operations Lead, you will own and continuously improve the AI Architecture Design process for all internal AI‑powered business products. You will lead a small, high‑impact operations function consisting of Technical Writers and an Operations Analyst, and you will partner closely with department leads and the AI CoE to drive process rigor, metrics, governance rhythms, and enablement. Your scope includes: standardizing ceremonies and artefacts, centralizing department KPIs and reporting, coordinating intake with the Portfolio team, curating the catalogue of reusable SDKs and platform offerings, and stewarding change management across the AI Architecture & Solution Design department. You will ensure that architecture excellence is repeatable: clear templates, consistent reviews, reliable evaluation coverage, well‑documented releases, and measurable flow from intake to approved design—while maintaining tight alignment with Embedded AI Architecture, Enterprise AI Capability Design, the Platform team, and the AI Engineering organization. Why this Role Matters This role is the operating system of the AI Architecture & Solution Design department. You provide the connective tissue that turns brilliant designs into repeatable, governable, and reusable practices at scale. By owning the design playbook, ceremonies, and measurement framework, you create the conditions for speed with safety—accelerating time to first value, increasing reuse of SDKs/modules/services, improving documentation quality, and ensuring that architecture decisions are auditable and aligned with enterprise controls. You enable department leaders to steer with data, teams to collaborate predictably, and product lines to benefit from platform thinking rather than bespoke one‑offs. Candidate Profile You are an operations‑minded leader who loves turning ambiguity into scalable systems. You blend architecture literacy with process excellence, and you’ve operated in matrixed environments where cross‑team alignment, portfolio coordination, and change management are daily realities. You are equally comfortable running a quarterly planning cadence, defining documentation standards with Technical Writers, partnering with architects on evaluation coverage, and rolling up dashboards for ELT/ELT‑1 stakeholders. You champion clarity, reusability, transparency, and continuous improvement, and you communicate with precision and empathy. ROLE RESPONSIBILITIES 1) Process Ownership & Operating Rhythms Own the AI Architecture Design Playbook (stages, gates, artefacts, RACI, and SLAs) and keep it current with department leads’ approval. Define and run core ceremonies (intake triage, architecture review boards, readiness checks, release note reviews, retrospectives, and communities of practice). Maintain standard artefacts & templates: ADRs, reference architecture templates, solution review checklists, evaluation/readiness checklists, risk registers, runbooks, release notes, and decision logs. Partner with the Portfolio team to manage funneling and prioritization of business use cases; ensure traceability from intake through design approval. Coordinate change management: publish process changes, version the playbook, communicate updates, and ensure adoption across sub‑teams. 2) Metrics, KPIs & Reporting Centralize department metrics and dashboards; enable leaders to steer with data. Example KPIs: Flow & velocity: cycle time from intake → architecture approval; time to first value. Quality & rigor: evaluation coverage, security/privacy readiness, documentation completeness. Reuse & leverage: reuse rate of SDKs/modules/platform services; reduction in bespoke components. Cost & performance: design‑stage cost/performance targets, observability and SLO readiness. Enablement & adoption: playbook adoption, template utilization, onboarding time, rotation program participation. Satisfaction: partner NPS / internal satisfaction for ceremonies, reviews, and artefacts. Publish a predictable reporting cadence (e.g., monthly ops review, quarterly outcomes review) consumable by department leads and ELT/ELT‑1 stakeholders. 3) Documentation Excellence & Knowledge Management Lead a team of Technical Writers to define standards for architecture documentation (writing style, minimal viable docs, diagrams, evaluation evidence, and release notes). Maintain a single source of truth for patterns, exemplars, ADRs, and design assets; ensure discoverability and lifecycle (versioning, archival, depreciation). Run documentation retrospectives with development pods; capture learnings from real engagements and feed them back into the playbook and templates. Ensure auditability: documentation supports security, compliance, and governance requirements. 4) Capability Catalogue & Reuse Enablement Curate and publish the catalogue of reusable SDKs, modules, and platform/managed services (internal and external), including ownership, maturity, versioning, and policy notes. Ensure parity expectations between SDKs and services are documented and understood; coordinate with the Platform and Enterprise AI Capability Design teams on gaps and roadmaps. Provide enablement content (blueprints, guides, exemplars, code samples) that raises design quality and accelerates adoption. 5) Cross‑Team Collaboration & Governance Coordinate with Embedded AI Architecture on review logistics, evaluation gate readiness, and alignment to reference patterns. Partner with Enterprise AI Capability Design to align capability roadmaps with field needs and to ensure SDK/service parity and extensibility. Work with the Platform team on service boundaries, SLO and observability readiness criteria, and design‑time security/privacy controls—without duplicating platform ownership. Liaise with the AI CoE and Portfolio to harmonize intake, prioritization, and cross‑program reporting. Support governance boards (agenda, inputs, decisions, outcomes) and maintain the decision trail. 6) People Leadership, Coaching & Community Lead, coach, and performance manage Technical Writers and an Operations Analyst; cultivate craftsmanship in documentation and measurement. Collaborate with the AI Solution Design Lead and Embedded AI Architecture Lead to standardize growth frameworks, competency models, and objective skill assessments. Nurture a culture of clarity, consistency, and continuous improvement grounded in feedback loops and transparent metrics. 7) Tooling & Automation for Operations Define and maintain the tooling backbone for operations (e.g., work tracking, documentation, dashboards, evidence repositories). Automate data capture for KPIs where possible (pipeline signals, evaluation runs, review outcomes, documentation status). Ensure tools and workflows are secure, compliant, and user‑friendly, with clear guidance and guardrails. BASIC QUALIFICATIONS 10+ years in operations excellence for software/AI organizations, solution/enterprise architecture operations, PMO, or engineering program management in matrixed enterprises. Demonstrated ownership of end‑to‑end operating models (process design, ceremonies, artefacts, metrics) across the AI/ML or software SDLC, including evaluation and release readiness. Proven experience producing executive‑grade reporting (ELT/ELT‑1), driving alignment, and leading change management across multiple stakeholder groups. Track record of improving flow, quality, and reuse via standardized playbooks, measurable KPIs, and effective knowledge management. Excellent communication and facilitation skills; adept at navigating governance (security, privacy, compliance) and enabling teams to move fast with safety. PREFERRED QUALIFICATIONS Background partnering with AI/ML, LLM/GenAI, and platform engineering teams; familiarity with evaluation frameworks, observability, and service SLO readiness at design time. Experience in large‑scale or regulated industries (e.g., healthcare, pharma, finance) with audit‑ready documentation and change control. Hands‑on familiarity with modern software delivery tooling (e.g., Jira/Azure DevOps, Confluence/Notion, data viz for dashboards) and with documentation standards for architecture artefacts. Experience defining and scaling competency models, growth frameworks, and rotation programs for architecture and solution design communities of practice. Exposure to MLOps/LangOps concepts, policy/guardrail integration, and data governance considerations as part of architecture design.