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AI Solution Architect-Research Office Managed Services

Huron Consulting · Chicago, IL · $155,000–$175,000 a year · Full time

Posted Jul 28, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about an AI solution you architected for a client. What design decisions mattered most?

What they are checking: Whether they can explain why they chose an architecture, not just which tools they used.

Tell me about a time a project's requirements changed late. How did you adapt the architecture?

What they are checking: The posting asks for adaptability, so they want to see flexible but sound design decisions.

How do you work with developers to make sure your architecture is built the way you intended?

What they are checking: Whether they stay involved through delivery rather than handing off a diagram.

What would you do

A university client is worried about sending grant data to an outside AI model. How do you address it?

What they are checking: Whether they take data privacy and institutional policies seriously and offer concrete options.

How do you explain an AI system's limits to a client who expects it to be always right?

What they are checking: Whether they set honest expectations that prevent misuse and disappointment.

About the work

How would you design a retrieval-augmented system to help research administrators answer sponsor policy questions?

What they are checking: Whether they can apply AI patterns to the research office context the role serves.

What do you know about research administration work, such as proposals, awards and compliance?

What they are checking: Whether they understand the business domain well enough to design useful solutions for it.

How do you test and monitor an AI solution once it's running in a managed services environment?

What they are checking: Managed services means ongoing support, so they want plans for evaluation, drift and incidents.

How do you decide when a simple rules-based solution is better than an AI one?

What they are checking: Whether they choose the simplest effective solution rather than reaching for AI by default.

How would you control cost when an AI solution's usage grows across many research offices?

What they are checking: Whether they think about token costs, caching and model choice as part of sound design.

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The full job description

As published by Huron Consulting.

Huron helps its clients drive growth, enhance performance and sustain leadership in the markets they serve. We collaborate with education organizations to develop strategies and implement solutions that enable the transformative change our clients need to own their future. Together, we empower clients to drive innovation, create sustainable funding streams and deliver better student outcomes. Today, leaders of higher education institutions and academic medical centers are spending too much time reacting to market forces, rather than focusing on the essential priorities that help students, faculty and staff thrive. The most productive path forward requires an intentional approach and innovative thinking, whereby stakeholders across the entire institution rally around a shared vision and embrace the hard work of effecting change. You’ll help our clients to achieve organizational effectiveness, improve student outcomes, implement new technologies and align resources and investments to ensure long-term sustainability. Join our team as the expert you are now and create your future. We are looking for a technically strong and adaptable AI Solution Architect to join our growing AI practice. In this role, you will contribute to the design and implementation of AI-powered solutions across a range of client-facing projects, helping ensure that architectural decisions are sound, scalable, and tailored to the problem at hand. You will work closely with engineering teams and client stakeholders to design AI systems that leverage traditional machine learning, generative AI, and intelligent automation. This role requires both a solid technical foundation and the ability to flex across different platforms, frameworks, and business needs. If you enjoy applying architecture principles to complex AI problems, working across multiple technologies, and collaborating with delivery teams to bring ideas into reality, this is a strong fit. Key Responsibilities • Support the architecture and design of AI solutions across multiple projects, ensuring technical feasibility and alignment with client goals • Contribute to the development of shared architectural patterns, reusable components, and design practices to support both experimental and production-ready AI initiatives • Evaluate client needs, system constraints, and platform environments to recommend scalable and secure AI designs across cloud, on-prem, or hybrid setups • Drive architectural decisions related to data pipelines, model orchestration, API development, observability, and integration with enterprise systems • Apply knowledge of traditional machine learning and generative AI technologies (e.g., LLMs, embeddings, RAG, AI agents) to support diverse solution needs • Understand and work with orchestration layers and protocols (e.g., tool use, function calling, and emerging standards like MCP) that support multi-step reasoning and agentic workflows • Serve as a technical resource to project teams by reviewing technical designs, contributing to code and system architecture, and mentoring junior engineers • Collaborate with delivery leads, and client stakeholders to refine solution designs as project requirements evolve • Participate in technology evaluation and internal discussions to help shape best practices and strengthen architectural consistency across teams Preferred Qualifications • 8+ years of experience in software engineering or AI/ML development, including 2+ years in solution design or architecture roles • Experience designing AI-powered solutions using machine learning, data pipelines, or generative AI APIs • Familiarity with enterprise architecture principles and working within production-oriented environments • Hands-on experience with Python, AI/ML frameworks, and API development • Exposure to GenAI frameworks and agent orchestration tools • Understanding of cloud platforms (Azure, AWS) and containerized environments • Comfort working in agile, project-based environments and collaborating with technical and non-technical stakeholders • Strong written and verbal communication skills; ability to translate between technical requirements and business goals • Certifications in Azure, Google Cloud Platform, or Amazon Web Services are highly desirable. • Bachelor’s degree in Computer Science, Engineering, or related field; advanced degrees or certifications are a plus The estimated base salary range for this job is $155,000 - $175,000.The range represents a good faith estimate of the range that Huron reasonably expects to pay for this job at the time of the job posting. The actual salary paid to an individual will vary based on multiple factors, including but not limited to specific skills or certifications, years of experience, market changes, and required travel. This job is also eligible to participate in Huron’s annual incentive compensation program, which reflects Huron’s pay for performance philosophy. Inclusive of annual incentive compensation opportunity, the total estimated compensation range for this job is $178,250 - $218,,750. The job is also eligible to participate in Huron’s benefit plans which include medical, dental and vision coverage and other wellness programs. The salary range information provided is in accordance with applicable state and local laws regarding salary transparency that are currently in effect and may be implemented in the future. #LI-JH1 #REMOTE Position Level Manager Country United States of America

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