New opportunity

AI Functional Consultant

Crowe Advisory LLC · Chicago, United States of America

About this role

The AI Functional Consultant supports client-facing AI projects by translating business needs into feasible solutions, with an emphasis on generative AI and the Microsoft ecosystem. The role works with business stakeholders and technical development teams to maintain clear requirements aligned with project goals.

Responsibilities

  • Participate in client workshops, training and requirements-gathering sessions; document business use cases, user needs, data needs and solution feasibility.
  • Help identify and prioritize AI use cases against business objectives. Explore data, test assumptions and support lightweight proofs of concept to assess technical constraints and data availability.
  • Draft and validate business, user, functional and non-functional requirements, user stories, acceptance criteria, test plans and supporting documentation. Assist with test execution and record outcomes.
  • Help translate client requirements into technical specifications, estimate effort, track tasks, timelines and deliverables, and communicate project status, risks and opportunities. Support training for clients and internal teams on GenAI capabilities.

Required qualifications

  • 1+ years in a client-facing or internship role. Understanding of generative AI and machine-learning fundamentals and their business applications; familiarity with Microsoft AI technologies and Power Platform.
  • Experience documenting clear, testable software requirements; awareness of product and software development lifecycles, including Agile or Waterfall. Strong analytical, problem-solving, client relationship and written and verbal communication skills.

Preferred qualifications and tools:

  • Business analysis techniques such as process and data models, use cases, storyboards and prototypes; technical documentation and professional-services experience.
  • Familiarity with Azure AI, Azure Machine Learning, Cognitive Services, prompt engineering, Enterprise ChatGPT, Microsoft Copilot, Azure AI Studio, AI Ops and Microsoft-environment DevOps practices. Microsoft Fundamentals certification, such as AI-900, or an introductory business analysis certification, such as ECBA, is recommended.

This is a full-time, 40-hour-per-week role in Chicago. The estimated salary range is $62,000–$100,000 per year; the disclosed estimate has not been adjusted for location-based differences. Crowe is not sponsoring work authorization at this time. Benefits include a comprehensive total rewards package and access to a Career Coach.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Generative AIMachine LearningBusiness analysisRequirements gatheringUse case prioritizationFeasibility analysisData analysisProof of concept developmentUser storiesAcceptance criteriaTest planningTest executionTechnical documentationStakeholder communicationClient relationship managementTraining deliveryPower PlatformAzure AIAzure Cognitive ServicesAgileWaterfallSoftware development lifecyclePrompt engineeringMicrosoft CopilotEnterprise ChatGPTAzure AI StudioDevOpsVersion controlAI Ops

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Get interview-ready for this role

A focused preparation guide, built around this job’s responsibilities and requirements.

✦ AI-generated guide
Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.
01

Understand the role

What matters most

  • Clarify client objectives and needs

    The role participates in workshops and requirements sessions, documents use cases and data needs, and helps stakeholders refine objectives. For preparation, practice turning a broad GenAI request into a clear business goal, user need and set of open questions.

  • Prioritize feasible AI use cases

    The consultant helps rank use cases against business goals and checks data availability and technical constraints through exploration, experiments and lightweight proofs of concept. Prepare to explain how evidence could support, narrow or rule out an idea.

  • Maintain testable requirements

    The posting emphasizes well-maintained, traceable requirements aligned with the solution vision, plus user stories, acceptance criteria and test outcomes. Prepare a concise example of moving from an ambiguous request to criteria a team could validate.

  • Connect client expectations to delivery

    The role assists as a liaison between functional and development teams, contributes to effort estimates, tracks tasks and timelines, and communicates status and risks. Prepare to describe how you would surface an unresolved requirement or constraint without implying the solution is settled.

  • Explain GenAI in the Microsoft context

    The role supports client and internal training on GenAI and ongoing learning in the Microsoft ecosystem. Prepare a plain-language explanation of a relevant GenAI use case, distinguishing foundational familiarity with Azure AI and Power Platform from the posting's preferred tools.

Likely challenges to think through

  • Business appeal versus demonstrable viability

    Likely preparation challenge, not a reported employer problem: a compelling use case may have uncertain data availability or technical feasibility. Prepare a way to rank its business value separately from feasibility, then propose a small experiment that tests the riskiest assumption.

  • Clear acceptance criteria amid AI uncertainty

    Likely preparation challenge: early-stage AI work is iterative, yet the role calls for testable, traceable requirements. Prepare to define observable outcomes and record test results while identifying assumptions that may require revision.

  • Stakeholder clarity versus delivery constraints

    Likely preparation challenge: client expectations may evolve while the team must estimate effort and track timelines and deliverables. Prepare to show how you would document a change, consult technical colleagues about its impact, and communicate the resulting trade-off.

03

Practice your answers

Technical practice

How would you capture an AI use case during a client workshop?

What to coverRole basis: The posting calls for documenting project objectives, user needs, data needs and feasibility for senior-team review. Suggested preparation: explain the questions you would ask and how you would record open assumptions rather than treating them as agreed requirements.

How would you help prioritize several proposed AI use cases?

What to coverRole basis: The role helps align use cases with business objectives and assess functional and technical feasibility. Suggested preparation: compare expected value, user need, data availability and constraints, while explaining what evidence you would need before recommending a priority.

When might generative AI be appropriate for a business need?

What to coverRole basis: Understanding GenAI and ML fundamentals and their business applications is required. Suggested preparation: distinguish generative from other ML applications at a basic level, and discuss the trade-off between useful outputs and the need to evaluate their reliability.

How would you test an assumption with data exploration or a lightweight proof of concept?

What to coverRole basis: The posting emphasizes checking data availability, exploring constraints and seeking to disprove assumptions through experimentation. Suggested preparation: define the assumption, a small test and a decision criterion, then explain how you would document inconclusive or negative findings.

How would you turn a business need into a testable user story?

What to coverRole basis: The role drafts user stories and acceptance criteria and helps keep requirements clear and traceable. Suggested preparation: show how you would link the story to a user need, specify observable acceptance criteria and validate the wording with stakeholders.

How would you identify functional and non-functional requirements for an AI solution?

What to coverRole basis: The posting asks for business, user, functional and non-functional requirements that are concise and testable. Suggested preparation: distinguish what the solution must do from constraints on how well it must work, and explain how you would resolve an ambiguous requirement before development.

How would you help plan and record functional testing?

What to coverRole basis: The role assists with test plans, test execution and capturing outcomes against functional requirements. Suggested preparation: describe deriving test cases from acceptance criteria, recording expected and actual outcomes, and escalating a mismatch for review.

How would you translate a client request into a specification for a technical team?

What to coverRole basis: The consultant assists as a liaison between functional and development teams. Suggested preparation: describe clarifying workflow, users, data and constraints, then checking the resulting specification with both teams before treating it as agreed.

How would you assess a Microsoft AI or Power Platform option for a use case?

What to coverRole basis: Basic familiarity with Azure AI and Power Platform is required; other Microsoft AI tools and prompt engineering are listed as preferred familiarity. Suggested preparation: explain how you would compare an option against the use case, available data and technical constraints without assuming any particular tool is mandated.

How would you support effort estimates when an AI project's scope is uncertain?

What to coverRole basis: The posting calls for team-based estimates, iterative early-stage AI work, and tracking tasks and timelines. Suggested preparation: discuss breaking work into testable steps, stating assumptions and revisiting estimates as proof-of-concept findings emerge.

Behavioural practice

Tell me about a time you clarified an ambiguous request with a stakeholder.

What to coverRole basis: The role relies on requirements gathering and validation to reduce ambiguity. Suggested preparation: use situation, action and result to show what you asked, how you confirmed shared understanding and what changed.

Describe a time you helped business and technical colleagues reach a shared understanding.

What to coverRole basis: Productive collaboration across business and development teams is a stated measure of success. Suggested preparation: give the situation, your actions to translate or reconcile different perspectives, and the result.

Tell me about a time evidence challenged an initial project assumption.

What to coverRole basis: The posting values data exploration and attempts to disprove assumptions during early solution work. Suggested preparation: explain the situation, how you investigated and communicated the finding, and the resulting decision.

Describe a time you communicated a project risk or delay.

What to coverRole basis: The role assists with tracking timelines and reporting status and risks to stakeholders. Suggested preparation: give the situation, your actions to make the risk clear and seek help or options, and the result.

Tell me about a time you learned a new technical concept and shared it with others.

What to coverRole basis: The posting emphasizes learning in the evolving AI landscape and supporting training or knowledge sharing. Suggested preparation: use situation, action and result to show how you checked your understanding, adapted your explanation to the audience and assessed whether it helped.

02

Sharpen your knowledge

Topics to prepare

  • Generative AI and ML business applications

    The posting requires understanding of GenAI/ML fundamentals and business applications. For revision, explain how each could address a hypothetical client need, what data it would need, and which assumptions would require testing.

  • Use-case prioritization and feasibility

    The role helps align AI use cases with business goals and assess technical constraints and data availability. For revision, compare two hypothetical use cases in a short decision table covering business value, data needs, constraints and unanswered questions.

  • Requirements and development lifecycles

    The posting calls for clear, testable business, user, functional and non-functional requirements, plus awareness of Agile or Waterfall. For revision, classify example requirements by type and explain how changes and validation would be handled in each lifecycle.

  • Microsoft AI ecosystem

    The posting requires familiarity with Power Platform and Azure AI; it also names Cognitive Services as an example of services encountered in the role. For revision, sketch where these fit in a hypothetical AI solution and note what you would need to confirm before selecting a service.

Skills to revise

  • Run a requirements-gathering conversation

    The role participates in client workshops and documents objectives, user needs and data needs. Practice a short mock stakeholder interview, then turn the answers into meeting notes with open questions for review.

  • Draft traceable requirements and user stories

    The posting emphasizes unambiguous requirements, user stories and acceptance criteria. Using a hypothetical use case, write a business objective, two user stories and measurable acceptance criteria; check that each criterion traces to a stated need.

  • Record a lightweight feasibility check

    The role supports data exploration, experiments and lightweight proofs of concept to test assumptions. As a preparation exercise, outline one assumption, the data needed to test it, a small test, its possible outcomes and how you would document a limitation.

  • Plan and capture functional testing

    The posting includes assisting with test plans, execution and outcome records. Practice converting one acceptance criterion into a test case with steps, expected result, observed result and a clearly recorded pass or failure.

  • Communicate project status across teams

    The role helps translate client needs for technical teams and tracks tasks, timelines and risks. Practice writing a brief status update for a hypothetical AI project that names a requirement clarification, its owner, a delivery risk and the next decision needed.

04

Your preparation checklist

  • Prepare a client workshop outline

    Posting: The role supports workshops and documents business use cases, user needs, data needs and feasibility. Preparation: Draft discovery questions and a one-page notes template that captures those findings and open decisions.

  • Build a use-case prioritization example

    Posting: The role helps align AI use cases with business goals and assess functional and technical feasibility. Preparation: Compare two clearly hypothetical use cases by business value, data availability, constraints and assumptions to test.

  • Walk through a relevant project or exercise

    Posting: The role supports data exploration, experimentation and lightweight proofs of concept. Preparation: Outline a real project if available, or label it hypothetical; show the question, data checks, experiment, findings and what remains unproven.

  • Draft requirements and a test example

    Posting: Clear, testable and traceable requirements, user stories, acceptance criteria, test plans and recorded outcomes are central to the role. Preparation: Create a small artifact set linking one business need to a story, acceptance criteria, test cases and an outcome log.

  • Rehearse a stakeholder handoff

    Posting: The consultant helps translate client needs for developers and communicates status, risks and opportunities. Preparation: Practice a brief explanation of your example for both audiences, including an unresolved question, a proposed next step and an effort estimate marked as provisional.

  • Review Microsoft AI fundamentals

    Posting: GenAI/ML understanding and familiarity with Power Platform and Azure AI are listed; several other Microsoft tools are preferred. Preparation: Make a short comparison of relevant capabilities and limits, and identify what you would need to verify before proposing a solution.

  • Write questions for the interviewers

    Posting: The role involves senior-team review, client training, iterative AI work and maintaining requirements. Preparation: Ask how use cases are evaluated, how requirements are validated with clients, and how consultants share POC findings with technical teams.

AI-generated from the job information · Prepared Oct 1, 2026 (UTC)Useful preparation, not a guarantee of eligibility or an offer.

Availability last checked: Nov 4, 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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