Job description

Enterprise Architect We are seeking an experienced Enterprise Architect for Data & AI to help shape the future of our SaaS platform. Data and AI are foundational to our customer experience, operational excellence, and long-term differentiation. This role ensures we scale intelligently, innovate responsibly, and treat data as a strategic product—not merely a byproduct of systems. The Enterprise Architect – Data & AI is a senior, strategic role responsible for defining and governing the enterprise-wide data and AI architecture that enables scalable SaaS growth, trusted analytics, and responsible AI adoption. This architect serves as a bridge between business strategy, data platforms, analytics, and AI/ML capabilities, partnering closely with product, engineering, security, compliance, and business leaders to translate vision into durable competitive advantage. What you ll do Enterprise Data & AI Strategy Define and maintain the enterprise data and AI architecture vision, principles, and roadmap aligned with business strategy and SaaS growth objectives Establish data-as-a-product practices, including ownership models, quality standards, SLAs, discoverability, and lifecycle management Guide strategic platform decisions across data ingestion, storage, processing, analytics, ML, and AI enablement AI Enablement & Responsible Governance Partner with product and engineering teams to embed AI/ML capabilities into SaaS products and internal workflows Define AI architecture patterns, such as feature stores, model lifecycle management, vector databases, and LLM integration Work with Chief Data & AI Officer to establish responsible AI guardrails, including governance, security, privacy, explainability, and regulatory compliance Collaborate with Chief Data & AI Officer, Security and Legal teams to align AI and data architectures with evolving regulatory requirements Architecture Governance & Standards Create and enforce enterprise standards and reference architectures for data platforms, analytics, and AI services Review and guide solution architectures to ensure scalability, interoperability, cost efficiency, and architectural consistency Balance near-term innovation with long-term architectural sustainability Business & Technology Alignment Translate business objectives into data and AI capabilities that drive measurable outcomes such as growth, efficiency, and customer experience Advise executives on data and AI investment decisions, trade-offs, and risk management Act as a trusted thought partner to senior leaders across product, engineering, and the business Platform & Cloud Architecture Guide cloud-native data and AI architectures across modern SaaS stacks, including event-driven, API-first, and multi-tenant environments Influence the evolution of data lakes, warehouses, streaming platforms, ML platforms, and AI services Optimize architectures for scalability, reliability, cost management, and vendor portability Change Enablement & Thought Leadership Evangelize data and AI best practices across the organization Mentor architects and senior engineers on data and AI architecture patterns What you ll bring 15 years of experience with 10 years of experience in enterprise, solution, or platform architecture, with deep focus on data and analytics Proven experience designing enterprise-scale data platforms in cloud-based SaaS environments Strong expertise in AI-enabled system architecture, including ML and/or Generative AI solution patterns Solid understanding of AI/ML architectures, including data pipelines, model lifecycle management, and integration patterns Hands-on familiarity with modern data technologies such as cloud data warehouses, data lakes, and streaming platforms Experience working across product, engineering, security, and business stakeholders Strong executive communication and storytelling skills Pragmatic familiarity with enterprise architecture frameworks (e.g., TOGAF) and architecture governance Proficiency in Agile and Lean delivery models Ability to deliver work which meets all minimum standards of quality, security, and operability. Preferred Attributes Experience enabling AI-powered SaaS products or large-scale analytics platforms Experience with LLMs, generative AI, and vector-based architectures Experience with data governance, privacy, and regulatory frameworks (e.g., SOC 2, GDPR, HIPAA, where applicable) Experience with data mesh or domain-oriented data architectures Background in a high-growth SaaS or platform company Experience with observability for data and AI, including quality, drift, lineage, and cost/usage Stay up to date on everything Blackbaud, follow us on Linkedin , X , Instagram , Facebook and YouTube Blackbaud powers social impact through purpose‑driven technology and responsible AI. Guided by our Intelligence for Good® vision, we’re building a culture where innovation, trust, and human expertise come together to help organizations make a greater difference in the world. Blackbaud is proud to be an equal opportunity employer and is committed to maintaining an inclusive work environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, physical or mental disability, age, or veteran status or any other basis protected by federal, state, or local law.

Requirements

Must-haves

Enterprise Architect
What you ll do
Enterprise Data & AI Strategy
Define and maintain the enterprise data and AI architecture vision, principles, and roadmap aligned with business strategy and SaaS growth objectives
Establish data-as-a-product practices, including ownership models, quality standards, SLAs, discoverability, and lifecycle management
Guide strategic platform decisions across data ingestion, storage, processing, analytics, ML, and AI enablement
AI Enablement & Responsible Governance
Partner with product and engineering teams to embed AI/ML capabilities into SaaS products and internal workflows
Define AI architecture patterns, such as feature stores, model lifecycle management, vector databases, and LLM integration
Work with Chief Data & AI Officer to establish responsible AI guardrails, including governance, security, privacy, explainability, and regulatory compliance
Collaborate with Chief Data & AI Officer, Security and Legal teams to align AI and data architectures with evolving regulatory requirements
Architecture Governance & Standards
Create and enforce enterprise standards and reference architectures for data platforms, analytics, and AI services
Review and guide solution architectures to ensure scalability, interoperability, cost efficiency, and architectural consistency
Balance near-term innovation with long-term architectural sustainability
Business & Technology Alignment
Translate business objectives into data and AI capabilities that drive measurable outcomes such as growth, efficiency, and customer experience
Advise executives on data and AI investment decisions, trade-offs, and risk management
Act as a trusted thought partner to senior leaders across product, engineering, and the business
Platform & Cloud Architecture
Guide cloud-native data and AI architectures across modern SaaS stacks, including event-driven, API-first, and multi-tenant environments
Influence the evolution of data lakes, warehouses, streaming platforms, ML platforms, and AI services
Optimize architectures for scalability, reliability, cost management, and vendor portability

Nice-to-haves

Preferred Attributes

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Platform: workday
Effort: long

Benefits

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