New opportunity

AI Engineer – Director

Chimney Sweep Masters · New York, United States

About this role

Lead AI solution development and transformation projects in New York, NY, using cloud AI services to improve customer experience, operational efficiency and decision-making across industries.

Responsibilities

  • Advise senior stakeholders, design and deliver multi-agent conversational AI and automation systems, and identify market opportunities through client engagement.
  • Manage and mentor cross-functional teams, foster innovation, and collaborate with Microsoft, Google and Salesforce platform teams to enhance AI capabilities.

Qualifications

  • At least eight years of experience in AI/ML, data analytics and cloud technology, with advanced knowledge of AI ecosystems on Microsoft, AWS or Google Cloud.
  • Ability to architect scalable AI solutions and integrate conversational AI, with an understanding of ethical AI practices.
  • An advanced degree in a related field, relevant certifications and authorization to work in the U.S. without sponsorship.

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

Skills for this role

Artificial IntelligenceMachine LearningData AnalyticsCloud TechnologyAI Solution ArchitectureMulti-Agent SystemsConversational AIAutomationEthical AIMicrosoft AzureAWSGoogle CloudSalesforceStakeholder ManagementTeam Leadership

Your skill match

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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

  • Translate AI strategy into business outcomes

    The posting calls for leading AI transformation projects that improve customer experience, operational efficiency and decision-making. Prepare to explain how you would connect a proposed solution to a measurable business outcome.

  • Deliver scalable conversational AI systems

    The role includes designing and delivering multi-agent conversational AI and automation systems, with scalable architecture and conversational AI integration named as essential skills. Prepare to walk through architectural decisions and how you would evaluate system performance.

  • Advise clients and identify opportunities

    The posting expects a trusted advisor to senior stakeholders who can identify market opportunities through client engagement. Prepare to explain how you would distinguish a valuable AI use case from one that is not ready to pursue.

  • Lead teams and platform collaboration

    Managing and mentoring cross-functional teams and collaborating with Microsoft, Google and Salesforce platform teams are stated duties. Prepare examples of aligning technical contributors and external platform partners around delivery decisions.

Likely challenges to think through

  • Balance agent autonomy with dependable delivery

    A likely challenge, not a stated employer problem, is that multi-agent automation can add coordination complexity while the role still requires scalable delivery and ethical AI practices. Prepare to discuss when a simpler design is preferable and how you would evaluate reliability and risks.

  • Navigate platform choices without losing business focus

    The posting names cloud AI ecosystems and collaboration with several platform teams. A plausible difficulty is weighing platform capabilities against integration effort and client needs. Prepare a decision framework grounded in the use case rather than a preferred vendor.

  • Pursue growth while protecting delivery capacity

    Client engagement and market opportunity identification sit alongside project delivery and team leadership. A likely trade-off is deciding which opportunities merit a team's attention. Prepare to explain how you would assess value, feasibility and delivery demands before committing.

03

Practice your answers

Technical practice

How would you architect a scalable cloud-based AI solution for a transformation project?

What to coverThe posting calls for scalable AI architecture and cloud AI services. Suggested answer focus: explain how you would separate components, plan for changing demand, and weigh performance, cost, and maintainability.

How would you design responsibilities and coordination in a multi-agent conversational AI system?

What to coverThe role includes designing and delivering multi-agent conversational AI systems. Suggested answer focus: describe how agents would divide work, share context, and handle conflicting or incomplete outputs.

How would you integrate conversational AI into an existing customer-facing experience?

What to coverConversational AI integration and improving customer experience are stated priorities. Suggested answer focus: address handoffs to existing services or people, response quality, and how you would avoid disrupting the user experience.

Which parts of a workflow would you automate with AI, and which would you leave under human control?

What to coverThe posting names automation systems and operational efficiency. Suggested answer focus: use task suitability, error consequences, and oversight needs to explain the boundary you would draw.

How would you use AI/ML and data analytics to improve decision-making?

What to coverAI/ML, data analytics, and improved decision-making appear in the posting. Suggested answer focus: define the decision first, then discuss data quality, a suitable analytical approach, and how users would interpret the result.

How would you evaluate whether an AI solution improves customer experience or operational efficiency?

What to coverBoth outcomes are explicit goals of the role. Suggested answer focus: propose a baseline and outcome measures, and distinguish measurable gains from shifts in workload or declines in quality.

How would you choose among Microsoft, AWS, or Google Cloud AI ecosystems for a solution?

What to coverThe posting seeks advanced knowledge of an AI ecosystem on Microsoft, AWS, or Google Cloud. Suggested answer focus: compare fit with the client's existing environment, integration needs, scalability, and cost rather than assuming one platform is always best.

How would you identify and investigate failures in a multi-agent conversational system?

What to coverDelivering multi-agent conversational systems is a stated responsibility; troubleshooting them is a suggested practice topic, not a stated duty. Suggested answer focus: trace where a response went wrong, separate coordination problems from individual component errors, and explain how you would test a fix.

How would ethical AI considerations affect the design of a conversational or automated solution?

What to coverThe posting explicitly calls for understanding ethical AI practices. Suggested answer focus: discuss privacy, potentially harmful or unfair outputs, transparency, and appropriate human oversight in relation to the proposed use.

Behavioural practice

Tell me about a time you advised senior stakeholders on an AI direction.

What to coverActing as a trusted advisor is a stated responsibility. Suggested answer focus: use a real situation, your advice and how you communicated trade-offs, and the resulting decision or outcome.

Describe a time you led a cross-functional team through a complex delivery.

What to coverThe role involves managing cross-functional teams and leading AI solution development. Suggested answer focus: explain the situation, how you aligned responsibilities and resolved friction, and the result.

Tell me about a time you mentored someone while fostering a new idea.

What to coverMentoring teams and fostering innovation are both stated duties. Suggested answer focus: give a real situation, the support or feedback you provided, and what changed as a result.

Describe a time you collaborated with an external platform team to improve a solution.

What to coverThe posting names collaboration with Microsoft, Google, and Salesforce platform teams. Suggested answer focus: explain the shared problem, how you coordinated technical and business priorities, and the outcome without implying you have worked with a particular named partner.

Tell me about a client engagement that revealed a new opportunity.

What to coverIdentifying market opportunities through client engagement is part of the role. Suggested answer focus: describe the client's need, how you assessed whether the opportunity was credible, what action you took, and the result.

02

Sharpen your knowledge

Topics to prepare

  • Multi-agent conversational AI

    Posting: The director designs and delivers multi-agent conversational AI and automation systems. Suggested revision exercise: compare when a multi-agent design is warranted versus a simpler conversational system, including coordination and failure-handling trade-offs.

  • Scalable cloud AI architecture

    Posting: The role calls for scalable AI solutions and advanced knowledge of AI ecosystems on Microsoft, AWS, or Google Cloud. Suggested revision exercise: explain how an architecture would handle rising demand, reliability, and integration; choose one of the named cloud ecosystems as the example.

  • AI/ML and analytics for business outcomes

    Posting: Cloud AI projects aim to improve customer experience, operational efficiency, and decision-making. Suggested revision exercise: map one proposed AI use case to a measurable outcome in each of those areas, distinguishing model performance from business impact.

  • Ethical AI practices

    Posting: Understanding ethical AI practices is essential. Suggested revision exercise: identify potential harms in a conversational AI use case and explain the review and oversight decisions you would raise before deployment.

  • AI transformation and client strategy

    Posting: The director advises senior stakeholders, leads transformation projects, and identifies market opportunities through client engagement. Suggested revision exercise: compare two potential client opportunities by value, feasibility, and delivery risk, then justify which to pursue first.

Skills to revise

  • Draft a solution architecture

    Suggested practice: sketch a multi-agent conversational AI and automation system, showing its components, integrations, and scaling decisions. This rehearses the posting’s design, delivery, and architecture responsibilities; the sketch is a preparation exercise, not a specified employer deliverable.

  • Plan platform collaboration

    Suggested practice: write a short integration plan identifying questions for Microsoft, Google, and Salesforce platform teams, and explain where expertise in one named cloud ecosystem would inform the design. The posting explicitly calls for collaboration with those teams; it does not require proficiency in every platform.

  • Present a stakeholder recommendation

    Suggested practice: prepare a brief executive recommendation for an AI initiative, stating the intended business outcome, key trade-offs, and a decision needed. This rehearses the advertised trusted-advisor and client-engagement duties.

  • Structure cross-functional delivery

    Suggested practice: outline responsibilities, decision points, and mentoring check-ins for a team delivering a conversational AI project. This relates to the posting’s requirement to manage and mentor cross-functional teams; the outline is suggested interview preparation.

04

Your preparation checklist

  • Map the stated qualifications to evidence

    The posting asks for at least eight years across AI/ML, data analytics and cloud technology, plus an advanced degree, relevant certifications and U.S. work authorization without sponsorship. Prepare a concise list of dates and documents to discuss, without assuming any particular certification is required.

  • Prepare an AI delivery walkthrough

    Choose a project you can discuss that is relevant to conversational AI or automation. Be ready to explain your role, design decisions, delivery challenges and measured effects on customer experience, efficiency or decision-making; these are outcomes named in the posting.

  • Practice a scalable AI architecture exercise

    The posting calls for scalable solutions, multi-agent conversational AI, cloud AI services and ethical AI practices. As preparation, sketch a hypothetical architecture on a Microsoft, AWS or Google Cloud ecosystem and explain integration, scaling, evaluation and risk controls.

  • Draft a senior-stakeholder briefing

    Prepare a short example of how you would explain an AI transformation proposal to senior stakeholders: the business problem, options, trade-offs and success measures. Advising stakeholders and identifying opportunities through client engagement are stated responsibilities.

  • Select a leadership and collaboration example

    Prepare one account of managing or mentoring a cross-functional team, including your decisions and the result. Also be ready to discuss how you would coordinate with platform teams such as Microsoft, Google and Salesforce, which the posting names.

  • Bring questions that clarify the scope

    Ask which customer or operational problems are priorities, what multi-agent systems are already in use, how platform-team collaboration works, and how the director role balances delivery, mentoring and client engagement. These are questions to investigate, not established company practices.

AI-generated from the job information · Prepared Sep 30, 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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