AI Solutions Engineer

Responsibilities

• AI Solution Design: Translates business and operational requirements into technical designs, solution options, implementation plans, and recommendations for AI-enabled services.
• Proof-of-Concept Development: Build and evaluate prototypes, pilots, automations, integrations, and proof-of-concepts using large language models, APIs, enterprise AI platforms, and related technologies.
• Prompt Engineering & Model Optimization: Designs, tests and refines prompts, workflows, retrieval patterns and model configurations to improve solution quality, usability, and reliability.
• Data & Integration Engineering: Develops and/or coordinates data flows, API integrations, connectors, and automation patterns required to support AI-enabled use cases.
• Architecture & Tool Selection: Advises on platform capabilities, vendor tools, build-versus-buy considerations, technical constraints, and scalable implementation approaches.
• Responsible AI & Governance Alignment: Partners with Security/Risk, Enterprise Architecture, data owners, accessibility partners, and other stakeholders to ensure solutions align with University policies and standards.
• Technical Documentation & Handoff: Creates technical documentation, implementation notes, support handoff materials, and reusable patterns to enable operational support and future reuse.
• Stakeholder Collaboration: Works closely with the AI Generalist, Emerging Technologies team members, faculty, staff, business units, vendors, and CUIT partners to deliver high-value solutions.
• Continuous Improvement: Identifies reusable components, accelerators, automation patterns, evaluation methods, and technical standards that improve the maturity of AIaaS delivery.

Qualifications

• Bachelor's degree and/or its equivalent required.
• Minimum 4-6 years’ related experience.
• Hands-on experience with programming or scripting languages such as Python, JavaScript, TypeScript, PHP, or similar languages.
• Experience building solutions with APIs, automation platforms, data pipelines, integrations, or cloud/enterprise platforms.
• Working knowledge of large language models, prompt engineering, AI application patterns, machine learning concepts, and responsible AI considerations.
• Demonstrated ability to translate business requirements into technical designs, prototypes, and production-ready or supportable solution approaches.
• Strong analytical, troubleshooting, documentation, and communication skills, including the ability to explain technical tradeoffs to non-technical stakeholders.
• Ability to manage multiple concurrent initiatives in a fast-paced, deadline-driven environment with changing priorities.
• Ability to work with minimal supervision and exercise sound judgment when handling sensitive, ambiguous, or high-visibility requests.
• Demonstrated ability to work in a fast-paced, deadline driven environment.
• Demonstrated excellence in a variety of competencies including teamwork/collaboration, analytical thinking, communication and influencing skills, and technical expertise.
• Ability to work with changing priorities and with multiple projects.
• Ability to be precise and attentive to detail is essential.
• Ability to work with minimal supervision and exercise sound judgment when handling sensitive, ambiguous, or high-visibility requests.
• Ability to work occasional evening/off-hour work as needed to support major launches, pilots, or critical service milestones.