What you’ll need to succeed?
· Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related discipline. A master’s degree is preferred.
· Enterprise architecture credentials such as TOGAF, IASA CITA, or an equivalent architecture certification are preferred.
· Relevant certifications in RPA, Microsoft Power Platform, workflow automation, process mining, AI, security, or related technologies are considered assets.
· 10 or more years of progressive architecture experience, including enterprise, domain, portfolio, application, or platform architecture responsibility.
· Significant experience designing, governing, and modernizing enterprise RPA, Intelligent Automation, workflow, or business process technology platforms.
· Deep expertise in at least one major Intelligent Automation capability and broad knowledge across RPA, Intelligent Document Processing, Microsoft Power Platform, process mining, workflow orchestration, Generative AI, and Agentic AI integration patterns.
· Demonstrated experience defining RPA and Intelligent Automation architecture strategies, future-state architectures, technology roadmaps, standards, reference architectures, and governance practices.
· Proven ability to collaborate with Technology Executives and influence senior business and technology leaders through clear analysis, architecture options, trade-offs, risks, and recommendations.
· Strong strategic thinking with the ability to translate business priorities, executive direction, regulatory obligations, operational risks, and technology constraints into actionable RPA and Intelligent Automation architecture direction.
· Knowledge of AI governance, AI risk management, responsible AI principles, privacy requirements, and enterprise AI adoption patterns as they apply to Intelligent Automation.
· Ability to assess automation requirements and determine the appropriate platform, integration pattern, architecture approach, governance controls, and delivery boundaries.
· Strong financial and analytical acumen, including investment prioritization, value realization, platform rationalization, technical debt, risk, and technology portfolio trade-offs.