Enterprise Architect

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