New opportunity

AI Consultant

Creatio · Boston, United States

About this role

Creatio seeks an AI Consultant to join its Boston office and help enterprise customers identify, design, and launch high-value AI agents with measurable business outcomes. The role combines business consulting, AI strategy, and solution design, working with AI engineers, product, solution engineering, sales, and customer success teams to support deployment, adoption, and scale.

Responsibilities

Develop customer AI adoption roadmaps and discover potential AI use cases. Learn each customer’s domain and processes, then prioritize opportunities by business impact and technical feasibility.
Translate business problems into solution concepts, requirements, and implementation proposals with success metrics and guardrails. Design AI agents and redesign workflows to reduce repetitive work.
Define integrations with enterprise systems, including CRM, ERP, SaaS applications, APIs, MCPs, and workflows. Produce agent specifications and solution documentation for delivery teams.
Collaborate across pre-sales, implementation, and adoption; support customer presentations and executive AI strategy discussions; and stay current with agentic AI trends and industry practices.

Requirements

Strong business analysis, process design, value mapping, and discovery skills; familiarity with modern LLMs, AI agent architecture, and business process automation; and comfort with APIs and integrations.
Experience in solution consulting, AI consulting, solution implementation, business consulting, or a similar customer-facing role. Hands-on experience designing or launching AI-powered solutions or agents, translating business requirements into solution designs, and working with enterprise customers and multiple stakeholders.
Excellent executive communication, presentation, analytical and systems-thinking skills, plus excellent spoken and written English.

Creatio describes flexible work arrangements, career development and mentorship, and a competitive compensation and benefits package that may vary by country of residence and employment type. No salary or specific work arrangement is stated.

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

Skills for this role

AI strategyAI adoption roadmapsAI agent designLLMsBusiness analysisProcess designValue mappingRequirements gatheringSolution designBusiness process automationAPI integrationCRMERPExecutive communicationPresentation skillsSystems thinkingEnglish

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Prioritize AI opportunities by value and feasibility
Discover each enterprise customer's domain and processes, identify AI use cases, and build adoption roadmaps based on business impact and technical feasibility.
Turn business needs into measurable solution plans
Translate opportunities into concepts, requirements, and implementation proposals with success metrics and guardrails. The role calls for business analysis, process design, and value mapping.
Design agents and implementation-ready workflows
Design AI agents that reduce repetitive work, redesign the surrounding workflows, define integrations with systems such as CRM and ERP, and document specifications for delivery teams.
Connect strategy, delivery, and adoption
Support executive AI strategy discussions and customer presentations while collaborating with sales, product, engineering, delivery, and customer success across pre-sales, implementation, and adoption.

Likely challenges to think through

Balancing impact with implementation effort
A likely challenge is choosing between an attractive use case and one that can be delivered sooner. Prepare a way to compare expected business value, process fit, integration effort, and technical feasibility without assuming every opportunity merits an agent.
Setting useful boundaries for agent autonomy
Because proposals need success metrics and guardrails, a likely design trade-off is how much work an agent should handle versus when a person should intervene. Prepare to explain how you would define the workflow, measure results, and specify boundaries before implementation.
Keeping proposals credible through delivery
The role spans executive discussions, specifications, implementation, and adoption. A likely difficulty is presenting a compelling strategy without losing the detail delivery teams need. Prepare to trace a business objective through requirements, integrations, agent specifications, and an adoption measure.

Practice your answers

Technical practice

Suggested practice: How would you discover AI agent opportunities in a customer's processes?

What to coverDescribe how you would learn the customer's domain, map a workflow, and identify repetitive work or unmet needs. Explain what you would validate with stakeholders before proposing an agent.

Suggested practice: How would you prioritize candidate AI use cases?

What to coverCompare expected business impact with technical feasibility, using value mapping and evidence from discovery. Explain how uncertainty or integration complexity could change the priority.

Suggested practice: How would you build a customer AI adoption roadmap?

What to coverShow how you would sequence use cases from initial opportunity through implementation and adoption. Suggest milestones tied to measurable outcomes, while making assumptions and dependencies visible.

Suggested practice: How would you turn a business problem into an agent proposal?

What to coverOutline the problem, solution concept, requirements, success metrics, and guardrails a proposal should contain. Explain how you would check that each element reflects the customer's intended business outcome.

Suggested practice: How would you design an AI agent using an LLM?

What to coverExplain the agent's intended task, the information and actions it needs, and where a person should retain control. Discuss how you would choose between an agent and simpler business process automation for the use case.

Suggested practice: How would you redesign a workflow around an AI agent?

What to coverDescribe which steps the agent could handle and which should remain with people or existing systems. Address handoffs, exceptions, and how the redesigned process would reduce repetitive work.

Suggested practice: How would you define an agent's enterprise integrations?

What to coverDescribe how you would identify the needed data and actions across CRM, ERP, SaaS applications, APIs, MCPs, and workflows where relevant. Explain how you would document dependencies, access boundaries, and failure handling for the delivery team.

Suggested practice: What would you include in an agent specification?

What to coverCover the intended outcome, workflow, requirements, integrations, guardrails, and success measures needed for implementation. Explain how you would resolve ambiguous requirements with the customer and delivery team.

Suggested practice: How would you assess an agent that is deployed but not delivering value?

What to coverCompare observed results with the agreed success metrics, then investigate the workflow, agent behavior, integrations, and adoption. Suggest how you would distinguish a design issue from a process or adoption issue before recommending changes.

Suggested practice: How would you evaluate a new agentic AI approach for a customer?

What to coverExplain how you would assess its relevance to a specific use case rather than adopting it because it is new. Compare potential value, feasibility, and guardrails with the existing solution concept.

Behavioural practice

Suggested practice: Tell me about a time you aligned stakeholders on a customer's business problem.

What to coverUse a real example with the situation, differing perspectives, your discovery and alignment actions, and the result. Focus on how you translated what you learned into a shared problem definition.

Suggested practice: Tell me about a time you prioritized competing solution opportunities.

What to coverDescribe the situation, how you assessed business value and feasibility, the recommendation you made, and the result. Make clear how you handled uncertainty or stakeholder disagreement.

Suggested practice: Tell me about a time you coordinated a customer-facing solution across teams.

What to coverSet out the situation, your actions with relevant commercial, product, or delivery colleagues, and the result. Explain how you maintained clarity about requirements and handoffs.

Suggested practice: Tell me about a time you presented a complex solution to executives.

What to coverUse a real situation, explain how you framed the business outcome and trade-offs, and describe the result. Include how you responded to questions or objections without overstating certainty.

Suggested practice: Tell me about a time you addressed an obstacle during solution launch or adoption.

What to coverDescribe the situation, the obstacle, the actions you took with the customer and delivery stakeholders, and the result. Explain what the experience changed about your approach to implementation or adoption.

Sharpen your knowledge

Topics to prepare

Use-case prioritization and value mapping
The posting calls for prioritizing customer AI opportunities by business impact and technical feasibility. Practice suggestion: compare three hypothetical CRM or workflow use cases, explain the value and feasibility of each, and rank them for an adoption roadmap.
LLMs, AI agents, and automation
The role requires familiarity with modern LLMs, AI agent architecture, and business process automation. Practice suggestion: explain when an agent would add value to a repetitive customer workflow, what actions it would take, and where human involvement would remain useful.
Enterprise integration concepts
The posting names CRM, ERP, SaaS applications, APIs, MCPs, and workflows as integration considerations. Practice suggestion: sketch how an agent could receive a workflow request, access relevant enterprise data, and pass an outcome to another system; identify integration assumptions that need validation.
Success metrics and guardrails
Solution concepts and implementation proposals must include success metrics and guardrails, with measurable customer outcomes. Practice suggestion: define an outcome measure, a baseline to establish, and two guardrails for a hypothetical agent-assisted workflow.
Adoption across the delivery lifecycle
The consultant works with sales, customer success, product, engineering, and delivery across pre-sales, implementation, and adoption. Practice suggestion: outline what each group would need to know or decide as an agent concept moves toward deployment and scale.

Skills to revise

Customer discovery and process mapping
The posting requires discovery, business analysis, and process design. Practice suggestion: draft interview questions for a hypothetical enterprise customer, then map its current workflow and mark repetitive steps and decision points.
Requirements and agent specifications
The role translates business problems into requirements and prepares agent specifications for delivery teams. Practice suggestion: write a one-page specification covering the workflow, agent actions, integration needs, success metric, guardrails, and open questions.
Solution proposal development
The posting calls for solution concepts and implementation proposals grounded in business impact and technical feasibility. Practice suggestion: turn one prioritized use case into a short proposal that explains the process change, expected value, dependencies, and decisions still needed.
Executive presentation
Customer presentations and executive AI strategy discussions are explicit responsibilities. Practice suggestion: deliver a three-minute explanation of a proposed agent, its measurable business outcome, main feasibility uncertainty, and recommended next step; then answer a skeptical stakeholder question concisely.

Your preparation checklist

Prepare an enterprise discovery plan
The role calls for understanding customer domains and processes. Draft questions that uncover workflow bottlenecks, stakeholders, existing systems, and constraints.
Build a use-case prioritization example
Prepare a sample AI adoption roadmap that ranks potential agents by business impact and technical feasibility. Label hypothetical assumptions clearly.
Walk through a relevant solution
If you have designed or launched an AI solution, prepare a concise account of the business problem, your contribution, design decisions, stakeholder input, and results. Otherwise, use a clearly labeled design exercise.
Draft an agent and integration specification
The role includes documenting agents for delivery teams. Sketch an agent’s tasks, workflow changes, and connections to relevant CRM, ERP, SaaS, API, or MCP systems; distinguish known facts from assumptions.
Define outcomes and guardrails
For your example, write an implementation proposal with measurable success criteria, a baseline to compare against, and safeguards appropriate to the proposed workflow.
Practice an executive explanation
Prepare a brief presentation that connects the proposed agent to business value, feasibility, and an adoption roadmap. Be ready to explain how you would collaborate with engineering, product, sales, and customer success.
Prepare questions for Creatio
Ask how this AI Consultant works across pre-sales, implementation, and adoption; what makes an agent specification useful to delivery teams; and how customers evaluate outcomes after launch.

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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