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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # AI Solutions Engineer - **Company:** DeVry University - **Location:** United States (Remote available) - **Experience:** Experienced - **Salary:** $120,000.0 - $125,000.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Application Programming Interfaces (APIs), Artificial Intelligence, Human Resources Information System (HRIS), JSON, Python (Programming Language), Regression Testing, Salesforce.Com, Microsoft SharePoint, Management of Software Versions, Scripting, Microsoft Power Automate, Large Language Models, Prompt Engineering, Generative AI, AI Platforms, Information Technology, Low-code, GPT - **Published:** May 23, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=60903dae825ff18e ## About the Role Do you have experience in Technical solutions implementation?, * 2+ years in applied AI, enterprise solution design, workflow automation, product enablement, or technical consulting roles involving LLM-based systems. * 5+ years of IT experience collaborating cross-functionally to deliver technology solutions that drive measurable operational improvements. * Experience translating business requirements into scalable AI-enabled workflows or enterprise solutions. * Hands-on experience designing and iterating prompts for tools such as Copilot, ChatGPT, or equivalent. * Experience with RAG pipelines, knowledge retrieval, or document ingestion workflows. * Ability to work rapidly and iteratively in ambiguous, fast-moving environments. * Strong communication skills and ability to translate stakeholder needs into prompt/agent behavior. * Experience using structured evaluation methods (rubrics, test cases, metrics) to assess AI output quality. Preferred * Familiarity with Python or low-code scripting for testing or API interactions. * Experience with Microsoft Copilot Studio, Salesforce GPT, or enterprise AI platforms. * Experience contributing to operational documentation or changing control processes. * Experience in higher education, EdTech, HR tech, or service operations. * Basic familiarity with higher-ed workflows (student services, HR, academics, IT support). * Understanding safety, compliance, and risk considerations in regulated environments. ## Description The Enterprise AI Solutions Engineer designs, implements, and optimizes AI-powered enterprise solutions that support DeVry's evolving AI ecosystem, including Copilot, ChatGPT, agentic workflows, and internal knowledge platforms. This role combines AI solution design, prompt engineering, Retrieval-Augmented Generation (RAG) optimization, workflow automation, and operational AI lifecycle management to improve enterprise efficiency, user experience, and service delivery across the organization. The ideal candidate can translate complex business processes into scalable AI-enabled solutions while ensuring output remains accurate, compliant, context-aware, and aligned with DeVry's institutional tone and policies. Key Responsibilities Enterprise Solutions * Design AI-enabled enterprise workflows that improve operational efficiency, user experience, and service delivery across institutional functions. * Collaborate with Product, IT, Security, HR, and Academic teams to identify and implement scalable AI solutions aligned to business objectives. * Evaluate and recommend AI platform capabilities, integrations, and workflow enhancements to support enterprise adoption and operational maturity. * Support enterprise AI initiatives by aligning prompt design, retrieval strategies, and automation workflows to broader organizational goals. Prompt Design & Optimization * Design and maintain high-quality prompts, and agent instructions for enterprise AI platforms. * Rapidly prototype and iterate prompt variants using structured experimentation, evaluation metrics, and A/B testing. * Build evaluation rubrics, structured test cases, and prompt datasets to measure accuracy, tone, consistency, and policy alignment. * Adapt prompts for higher-education use cases (e.g., advising, HR, faculty support, IT, student services) while maintaining institutional tone and compliance. RAG & Knowledge Integration * Curate and manage document ingestion, embeddings, and knowledge base updates to ensure relevant, current, and context-aware responses. * (Optional) Maintain and optimize Retrieval-Augmented Generation (RAG) pipelines supporting policy retrieval, HRIS lookups, Salesforce case context, and SharePoint knowledge sources. * (Optional) Define structured output formats (e.g., JSON) when required for automated workflows. AI Operations (Lightweight AIOps) * Support the lifecycle of prompts and agents, including change control, versioning, and regression testing. * Monitor usage, output quality, knowledge retrieval performance, and drift to detect issues early. * Participate in lightweight incident response and safe rollback processes when AI behaviors degrade or become noncompliant. * Maintain operational runbooks and documentation to ensure long-term maintainability and continuity. Governance, Safety & Compliance * Implement guardrails and safety rules to minimize hallucinations, unsafe content, and policy violations. * Identify and mitigate issues related to bias, tone, safety, and factual accuracy. * Ensure AI usage adheres to institutional policies, compliance requirements, and risk standards. Cross-Functional Collaboration * Serve as a strategic partner between business stakeholders and technical teams, translating operational workflows and enterprise needs into scalable AI-enabled solutions, prompt strategies, and intelligent automation opportunities. * Partners with HR, Student Services, Academics, IT, Product, and Security teams to design AI-supported processes with measurable impact. * Communicate findings clearly and concisely to non-technical audiences. Continuous Improvement * Stay up to date on prompting techniques, LLM capabilities, and platform enhancements. * Drive incremental improvements in agent reliability, workflow automation, and operational consistency. * Contribute to standardized prompt frameworks, reusable templates, and prompt libraries. ## Related Videos - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [ Evaluating AI models for code comprehension](https://www.wearedevelopers.com/videos/1462-evaluating-ai-models-for-code-comprehension) - [Tips and Tricks for Working with JSON](https://www.wearedevelopers.com/videos/1229-tips-and-tricks-for-working-with-json) - [Reimagining app development with Low-code and AI](https://www.wearedevelopers.com/videos/1651-reimagining-app-development-with-low-code-and-ai) - [Dynamic Entities in .NET: Building Low-Code Systems on Top of Entity Framework Core](https://www.wearedevelopers.com/videos/100218-dynamic-entities-in-net-building-low-code-systems-on-top-of-entity-framework-core) - [What If Apps Built Themselves? 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