Enterprise AI Solutions Architect

Responsibilities

• Defines and drives the Bank’s enterprise AI solution architecture, technical standards, and reference patterns.
• Translates business needs and AI strategy into practical architecture decisions, platform recommendations, and implementation guidance.
• Evaluates architectural tradeoffs across models, hosting approaches, vendors, orchestration methods, integration patterns, and control requirements.
• Determines the best fit for purpose, supportability, and alignment with the Bank’s security, risk, and regulatory expectations.

Qualifications

• Bachelor’s degree in computer science, information systems, engineering, technology architecture, aata/AI, or related field; or equivalent combination of education and professional experience required.
• Advanced degree in computer science, engineering, information systems, data science, artificial intelligence, or related discipline preferred.
• Cloud, architecture, security, or AI-related certifications preferred.
• 10+ years of experience in enterprise architecture, solution architecture, software engineering, or related technical design roles; and 3+ years of experience designing, evaluating, or implementing AI/ML, generative AI, intelligent automation, or advanced analytics solutions in an enterprise environment.
• Strong hands-on experience with cloud architecture, APIs, enterprise integration patterns, security design, and production solution delivery.
• Demonstrated experience making architecture tradeoff decisions across platforms, vendors, hosting models, and implementation patterns.
• Experience reviewing and approving technical designs and providing architecture leadership across cross-functional teams.
• Experience operating within a regulated environment, preferably financial services.
• Demonstrated understanding of AI and emerging AI solution patterns, including capabilities, limitations, implementation considerations, and associated operational and risk implications.
• Experience designing architecture for copilots, retrieval-based solutions, workflow automation, agentic solutions, document intelligence, or decision-support capabilities.
• Experience with model orchestration, enterprise AI platforms, observability, access controls, and production support considerations for AI systems.
• Experience influencing platform selection, vendor evaluation, and enterprise technology direction.
• Familiarity with banking systems, internal operations, and enterprise use cases in regulated environments.