Director Enterprise Architecture

Description -

About HP

At HP youll have a chance to create tools technology and solutions that reshape the way the world works in the future. If youre looking to join a company that allows you to connect with a network of professionals eager to support you in doing your best work we want to talk to you. Our legendary culture guides every employee toward successfostering collaboration and driving innovation.

Operating in over 170 countries HP is always creating new services products and capabilities giving you more opportunities to advance your career. Here innovation is the key to professional development and career mobility.

When you join HP youre joining a company that believes every voice matters and that we all deserve a seat at the table. From the boardroom to factory floor we create a culture where everyone is respected and where people can be themselves. You will be part of a global laboratory where different perspectives and experiences will help you solve problems in new ways. This is where you can build a long and wide-ranging career.

Role Description

The Director Enterprise Architecture (EA) is a senior leadership role responsible for defining and governing the enterprise-wide technology architecture that enables business strategy digital transformation and AI-enabled innovation at scale. This role serves as the connective tissue between business strategy and technology execution ensuring that architecture decisions accelerate simplification operational efficiency risk reduction and long-term value creation.

The Director leads the Enterprise Architecture function as a strategic advisory capability setting architectural vision standards and governance while partnering closely with executive leadership business leaders and technology teams across the enterprise.

Responsibilities

Enterprise Architecture Strategy & Vision

• Define and own the enterprise architecture vision principles and target-state roadmaps aligned to business strategy and long-term objectives.
• Translate an AI-forward and digital-first strategy into actionable architectural blueprints spanning business data application integration and technology domains.
• Ensure architecture decisions enable scalability security resilience and cost efficiency across the enterprise.

Application & Technology Portfolio Optimization

• Drive enterprise-wide application portfolio rationalization using structured frameworks (e.g. TIME) reducing redundancy technical debt and operational complexity.
• Establish end-to-end application lifecycle governance to ensure new investments align with enterprise standards and strategic priorities.
• Guide build-versus-buy and platform decisions to maximize reuse interoperability and long-term return on investment.

AI Data and Integration Architecture Enablement

• Partner with data platform and security leaders to define reference architectures that enable scalable AI analytics and automation capabilities.
• Establish architectural patterns for integration APIs data platforms and AI orchestration that support rapid innovation while maintaining enterprise-grade controls.
• Ensure AI solutions are designed with economic sustainability governance and risk management in mind.

Architecture Governance Risk & Compliance

• Establish and lead enterprise architecture governance including architecture review boards standards and decision frameworks.
• Embed security-by-design data governance and regulatory requirements directly into architecture standards to reduce risk and audit burden.
• Prevent fragmentation and shadow IT/AI by enabling compliant self-service architectural patterns.

Leadership & Operating Model

• Lead and develop a high-performing Enterprise Architecture organization including senior architects and architecture leaders.
• Evolve the EA function from a standards-focused role into a trusted strategic advisory capability.
• Promote modern ways of working reusable patterns and community-of-practice models across the technology organization.

Strategic Impact & Decision Authority

• Influences and shapes long-term technology and digital strategy across multiple business units and functions.
• Makes final decisions on enterprise architecture standards frameworks and major architectural direction.
• Owns architectural policies and governance mechanisms that directly impact business agility cost structure risk posture and technology outcomes.
• Accountable for effective delivery of enterprise architecture objectives and measurable business outcomes.

Strategic Impact & Decision Authority

• Influences and shapes long-term technology and digital strategy across multiple business units and functions.
• Makes final decisions on enterprise architecture standards frameworks and major architectural direction.
• Owns architectural policies and governance mechanisms that directly impact business agility cost structure risk posture and technology outcomes.
• Accountable for effective delivery of enterprise architecture objectives and measurable business outcomes.

Problem Solving & Innovation

• Addresses highly complex ambiguous and enterprise-wide challenges that span multiple domains geographies and platforms.
• Simplifies large-scale technology ecosystems to enable speed resilience and cost efficiency.
• Anticipates emerging technologies and industry trends translating them into practical architectural strategies.
• Balances competing priorities across speed-to-market cost security and scalability.

Scope of Accountability

• Enterprise-wide scope across business units functions and geographies.
• Ownership of enterprise architecture standards roadmaps and governance.
• Accountability for architecture-related planning staffing prioritization and budget inputs.
• Decisions have long-term impact on business performance technology investment and operational risk.

Education

• Bachelors degree in Computer Science Information Systems Engineering or related technical discipline (required).

Professional Experience

• 15 years of progressive IT leadership; minimum 8 years in enterprise architecture at Fortune 500 or global enterprise scale.
• Demonstrated experience leading EA functions with 20 architects across multi-geo matrixed environments; accountability for $100M IT portfolios.
• Proven track record delivering enterprise AI adoption programs end-to-end: strategy platform selection implementation scaling and value realization.
• Hands-on experience architecting and deploying Generative AI and Agentic AI solutions in production enterprise environments.
• Experience driving AI-enabled productivity programs with quantifiable outcomes cost reduction cycle time compression or revenue enablement.
• Track record of application rationalization legacy modernization (ERP mainframe) and cloud migration on a global scale.
• Background in digital value chain transformation (Lead-to-Order Order-to-Cash Acquire-to-Decommission) in a technology product company is highly desirable.
• Experience in M&A technology due diligence and integration architecture is a plus.
• Demonstrated C-suite and Board-level engagement on technology strategy and investment decisions.

Skills and experience

Knowledge

• TOGAF 9.2 / 10 Certified or Distinguished level Zachman Framework Certification (preferred)
• SAFe (Scaled Agile Framework) Architect ITIL 4 Managing Professional or Strategic Leader
• AWS Solutions Architect Professional Azure Solutions Architect Expert
• Microsoft Certified: Azure AI Engineer Associate or Azure AI Fundamentals AWS Certified Machine Learning Specialty
• Enterprise AI governance programs: NIST AI RMF Practitioner Responsible AI Institute certifications

Enterprise and AI architecture

• Expert-level command of TOGAF Zachman FEAF and Gartner EA frameworks; Architecture Development Method (ADM) and EA governance models.
• Business Architecture: capability modeling value stream mapping and operating model design.
• Application Architecture: portfolio rationalization (Gartner TIME model) modernization patterns LeanIX and ServiceNow SPM.
• Data Architecture: data mesh data fabric MDM enterprise data governance and Lakehouse patterns (Snowflake Databricks).
• Security Architecture: zero-trust IAM threat modeling and privacy-by-design.
• Proficiency in architecture tooling: ArchiMate BizzDesign Lucidcharts and executive-grade visual storytelling.
• Deep expertise designing enterprise AI reference architectures: model serving layers LLM orchestration (LangChain LlamaIndex Semantic Kernel) vector databases (Pinecone Weaviate pgvector) and retrieval-augmented generation (RAG) pipelines.
• Agentic AI architecture: multi-agent orchestration frameworks (AutoGen CrewAI) tool-use patterns memory and context management and human-in-the-loop design.
• AI platform architecture across leading enterprise stacks: OpenAI Frontier Microsoft Azure OpenAI / Copilot Studio Anthropic Claude Salesforce Agentforce ServiceNow AI Control Tower and Google Vertex AI.
• MLOps and AI engineering: model lifecycle management CI/CD for AI feature stores model registries drift detection and observability.
• Edge AI and on-device inference architectures - PC print and 3D manufacturing device portfolios.
• AI data architecture: synthetic data generation data labeling pipelines training data governance and inference data privacy.

Enterprise AI Adoption & Value Realization

• Proven methodology for scaling AI from proof-of-concept to enterprise production: adoption playbooks change management integration and user enablement frameworks.
• AI business value modeling: ROI quantification productivity gain measurement cost-per-inference optimization and AI TCO frameworks.
• Experience establishing AI Centers of Excellence (AI CoE): operating model design talent strategy toolchain standardization and governance integration.
• AI FinOps: token economy management GPU/compute cost allocation model selection trade-off analysis (cost vs. latency vs. accuracy) and chargeback models.
• Practical knowledge of AI integration patterns: API-based inference embedded AI in business workflows (ERP CRM ITSM) and AI-native application design.
• Experience measuring and communicating AI value realization to executive and board audiences through KPIs dashboards and business outcome narratives.

AI Governance Risk & Responsible AI

• Comprehensive knowledge of NIST AI Risk Management Framework (AI RMF) and its operationalization within enterprise governance structures.
• Familiarity with EU AI Act requirements AI liability frameworks and global AI regulatory trends affecting enterprise technology deployment.
• Responsible AI principles in practice: bias detection and mitigation model explainability (XAI) fairness metrics and auditability by design.
• AI security architecture: prompt injection defense adversarial ML model poisoning prevention and secure AI deployment patterns.
• Data privacy in AI: PII handling in training and inference differential privacy techniques and consent management for AI systems.
• AI audit and compliance: model cards system cards AI impact assessments and third-party model risk evaluation.

Cloud Infrastructure & FinOps

• Multi-cloud architecture expertise (AWS Azure GCP): cloud-native design serverless event-driven and microservices patterns.
• AI-optimized infrastructure: GPU cluster design inference optimization (quantization distillation) and AI-forward network architecture.
• Containerization and orchestration: Kubernetes Docker and AI workload scheduling.
• FinOps / TBM: cloud cost governance AI compute spend optimization and IT spend transparency.

Integration Data & Modernization

• API-first design and integration architecture: MuleSoft Azure Integration Services Boomi.
• Legacy modernization: SAP S/4HANA transformation mainframe migration application decommissioning.
• ITAM/SAM/CMDB and Acquire-to-Decommission (A2D) lifecycle governance.
• GRC platforms: ServiceNow GRC RSA Archer; regulatory frameworks: SOX ITGC GDPR data residency.

Leadership & Executive Communication

• Executive presence: ability to influence C-suite and board on complex AI and technology strategy decisions.
• Team building: recruit mentor and scale globally distributed architecture teams across disciplines.
• Organizational change management for AI-driven transformation in large matrixed enterprises.
• Thought leadership: publications advisory council participation (e.g. HBR Forbes Tech Council) and external industry representation.
• Strong OKR/KPI development linking architecture and AI investments to measurable business outcomes.

Benefits:

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Equal Opportunity Employer (EEO) -

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