Principal Enterprise Architect - Innovation

Scope:

• Lead the enterprise AI architecture strategy by designing scalable, secure, and responsible AI solutions that align with business objectives.
• Drive AI governance, MLOps, data platforms, and cloud infrastructure to enable organization-wide AI adoption and innovation. Partner with business and technology leaders to deliver intelligent systems, automation, and data-driven solutions that generate measurable business value.

What You’ll Do:

• Develop and communicate a clear AI architectural vision and strategy aligned with the organization's business objectives, competitive advantage, and responsible AI principles, ensuring alignment with emerging AI trends and technological capabilities.
• Establish and maintain comprehensive AI governance frameworks, including policies, standards, guidelines, and best practices for AI development, model governance, data management, and responsible AI deployment across the organization.
• Design and oversee the development of enterprise AI solutions that translate business requirements into intelligent systems architecture, translating business needs into technical and data requirements that drive measurable business outcomes.
• Ensure the quality and readiness of AI implementations by evaluating AI technologies, platforms, and tools, architecting modern, scalable, and future-ready AI stacks that leverage current and emerging capabilities.
• Design and implement resilient AI systems and data pipelines that incorporate appropriate levels of data protection, governance, disaster recovery, and business continuity for mission-critical AI services and operations.
• Deliver AI proof-of-concepts, provide guidance on AI development practices, conduct model and architecture reviews, evaluate AI vendors and technologies, and partner with technology providers to advance the organization's AI capabilities.
• Design and implement enterprise data integration platforms and data pipelines that enable seamless data flow, interoperability, and data readiness across disparate systems to support AI and analytics initiatives.
• Architect and oversee the development of AI-powered enterprise applications and intelligent automation solutions that optimize business processes, enhance decision-making, and improve operational efficiency at scale.
• Lead the development of AI infrastructure, MLOps platforms, cloud architectures, and security frameworks that solve complex challenges and drive enterprise adoption of AI. Contribute to and leverage the architecture repository to enforce governance of AI principles, standards, reference architectures, and solution patterns.
• Lead and mentor high-performing individuals within enterprise architecture and technology functions, fostering AI literacy, building technical capability, and cultivating a culture of responsible innovation across the organization.

What We’re Looking For:

• Bachelor’s degree in computer science, Information Technology, Engineering, Data Science, or a related field.
• At least 15+ years of experience in technology roles with strong expertise in AI architecture, machine learning platforms, cloud infrastructure, and enterprise data engineering.
• At least 7+ years in a leadership, Principal Architect, or Chief Architect role with proven success driving AI and intelligent systems strategy across the enterprise.
• Deep expertise in enterprise AI and machine learning architecture, including platform design, MLOps frameworks, model governance, and responsible AI governance structures.
• Proficiency in cloud AI/ML services and platforms (e.g., AWS SageMaker, Azure ML, Google Cloud AI, Databricks) and experience architecting AI solutions on enterprise cloud infrastructure.
• Strong experience with ML platforms, orchestration tools, and model management solutions (e.g., MLflow, Kubeflow, feature stores, model registries).
• Expertise in enterprise data platforms, data engineering, data warehousing solutions, and analytics technologies that enable AI and advanced analytics at scale.
• Proven understanding of AI governance frameworks, model monitoring, model explainability, and responsible AI principles including bias detection, fairness, and compliance.
• Experience with enterprise integration platforms and data pipelines (e.g., MuleSoft, Boomi, Apache Airflow, Spark) that support data flow and interoperability for AI initiatives.
• Demonstrated expertise in cloud security, data protection, and compliance frameworks as they apply to AI systems, including data governance and regulatory requirements.
• Knowledge of AI-powered enterprise applications and intelligent automation solutions (e.g., intelligent process automation, AI-driven CRM, predictive analytics platforms).

Our Values

If you want to know the heart of a company, take a look at their values. Ours unite us. They are what drive our success – and the success of our customers. Does your heart beat like ours? Find out here: Core Values

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.