AI Solutions Architect
Listed on 2026-07-21
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IT/Tech
AI Engineer (Applied/Software), AI Business & Operations
Engineering a world of possibilities. The AI Solutions Architect drives the rapid development, integration, and scaling of AI‑powered solutions that align with institutional goals and regulatory requirements. This role bridges the gap between university needs and technical capabilities, translating emerging AI technologies, including agentic AI, into secure, ethical, and user‑centered tools that enhance academic, administrative, and operational outcomes.
PLEASE NOTE:
This position is not eligible for visa sponsorship now, nor in the future. This is an individual contributor role with high visibility and impact, requiring both strategic vision and hands‑on technical execution to create and maintain AI agents, perform system and data integrations, and validate outputs for accuracy and reliability. The role is currently hybrid and requires regular commuting to campus.
Responsibilities AI Integration, Enablement & Governance
- Embed AI tools into university systems and business processes to ensure successful adoption.
- Integrate Microsoft, Google, and other approved AI services into workflows.
- Support onboarding, training, and change management for responsible AI use.
- Ensure compliance with Mines data governance and AI policies.
- Contribute to AI governance frameworks, including model transparency and risk mitigation.
- Develop, deploy, and align AI solutions with institutional goals and long‑term value.
- Identify and fast‑track opportunities for AI‑driven innovation that enhance academic programs, student experiences, and operational efficiency.
- Accelerate the full lifecycle of AI product development, from discovery and prototyping to deployment and iteration.
- Understand product roadmaps and assess features, technical feasibility, and overall institutional value.
- Translate complex AI concepts (e.g., large language models, prompt engineering, RAG, AIOps) into actionable product strategies.
- Develop and track key performance indicators (KPIs) and user feedback to measure the success and impact of AI initiatives.
- Emphasize cross‑functional engagement and build AI fluency across the institution.
- Establish relationships and partner with academic, administrative, and IT stakeholders to implement requirements and align AI solutions with institutional goals.
- Serve as a liaison between technical teams and end users to ensure clear communication and shared understanding.
- Contribute to AI literacy initiatives by developing documentation, training resources, and awareness campaigns for faculty, staff, and students.
- Bachelor’s degree from a four‑year college or university in computer science, data science, information systems, engineering, or a related field. Individuals without a degree may be considered if they demonstrate possession of substantially the same knowledge level as found in a degree but have attained the advanced knowledge through a combination of work experience and intellectual instruction.
- 3+ years of experience in one or more of the following areas: product ownership in a technology‑driven environment, AI architecture or implementation (including ML development or implementation), business analysis or digital transformation, data analytics, data governance, or data strategy, technology enablement or IT project management.
- Strong understanding of AI/ML concepts, including generative AI, prompt engineering, and model evaluation.
- Ability to translate complex technical concepts into actionable strategies for diverse stakeholders.
- Familiarity with cloud‑based AI platforms (e.g., Microsoft Azure, Google Cloud, AWS).
- Knowledge of data privacy and compliance frameworks (e.g., FERPA, HIPAA, GDPR).
- Excellent communication, collaboration, and stakeholder engagement skills.
- Demonstrated ability to lead cross‑functional initiatives and drive organizational change.
- Eagerness to learn agentic AI skills that will immediately be put to use.
- Self‑starter with a high degree of initiative, accountability, and adaptability.
- Master’s degree in a related field.
- Experience managing AI or data‑driven products in complex, regulated…
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