Artificial Intelligence & Automation Architect
Why This Role Stands Out
Shape the future of AI and automation at a leading university system, designing enterprise architecture frameworks that drive innovation across academic, research, and administrative functions. You'll thrive in this hybrid role if you possess deep technical expertise in AI, cloud, and integration, coupled with a passion for establishing robust governance and security practices. This is an exceptional opportunity to develop cutting-edge skills and make a significant impact in a respected institution.
Quick Overview
Job Description
Job Summary
The AI and Automation Architect is responsible for designing, governing, and advancing the architectural frameworks, platforms, integration patterns, and technical controls that enable secure, scalable, and responsible artificial intelligence and intelligent automation across the Institute. This role establishes enterprise architecture standards, governance practices, and lifecycle controls that support academic, research, student, and administrative initiatives while ensuring alignment with institutional requirements for data governance, privacy, cybersecurity, accessibility, compliance, reliability, and risk management.
Job Summary
This position is at the level of Lead Professional, emphasizing enterprise-scale architecture and deep technical expertise that informs and enables institutional AI, data, governance, and platform strategies set by senior leadership. For more information on this level, please visit URL
Responsibilities
Job Duty 1 -
Design cloud, integration, and platform architecture standards that connect AI, machine learning, and automation solutions with enterprise data, systems, and applications.
Job Duty 2 -
Define and maintain security architecture and controls: identity, access, network isolation, encryption, secrets management, and data-loss prevention for the enterprise AI and automation platform.
Job Duty 3 -
Implement technical safeguards against AI-specific risks, including prompt injection, sensitive-data exposure, insecure tool use, excessive agent permissions, model or supply-chain compromise, and unauthorized AI services.
Job Duty 4 -
Evaluate AI, cloud, integration, and automation technologies using documented criteria for capability, security, privacy, accessibility, risk, supportability, continuity, and cost.
Job Duty 5 -
Architect data retrieval and grounding strategies, including retrieval-augmented generation and data pipelines, that allow AI and automation tools to consume Institute data accurately and securely, in alignment with data governance standards.
Job Duty 6 -
Lead collaborative design sessions and architecture reviews to align AI and automation solutions with institutional goals, stakeholder needs, and approved architecture standards.
Job Duty 7 -
Translate AI governance requirements into enforceable architecture standards, documentation practices, technical controls, and lifecycle processes for AI models, automation workflows, and integration components.
Job Duty 8 -
Provide technical guidance, mentoring, and training on cloud, AI, and automation architecture practices, and maintain current knowledge of emerging technologies.
Job Duty 9 -
Oversee architecture assessments and define platform requirements for capacity, performance, resilience, disaster recovery, scalability, service objectives, and observability for the enterprise AI and automation platform.
Job Duty 10 -
Perform other duties as assigned.
Required Qualifications
Educational Requirements
Bachelor's degree in related discipline or equivalent, related experience
Required Experience
6+ years of relevant experience
Preferred Qualifications
Preferred Educational Qualifications
Master's degree in related discipline or equivalent, related experience
Preferred Qualifications
Preferred Experience
Experience designing or operating production AI, machine learning, generative AI, or intelligent automation capabilities in a complex organization.
Experience architecting agentic AI systems, including tool integration, orchestration, and human oversight controls.
Experience with major cloud platforms (e.g., AWS, Azure, Google Cloud) and enterprise API or integration frameworks.
Experience establishing architecture standards, reference architectures, or review processes adopted across multiple teams.
Experience translating governance, security, privacy, or compliance requirements into technical controls and auditable evidence.
Experience supporting higher education, research, healthcare, government, or large enterprise environments.
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