Enterprise Architect

Saved 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

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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.