Cross Functional Collaboration and Partnership Questions

How to form and operationalize partnerships across adjacent functions to deliver cross functional objectives. Covers identifying key partners such as engineering design product research operations and marketing, understanding their goals constraints and decision rights, involving technical and design partners early, balancing product vision with feasibility, and aligning priorities across teams. Includes governance and coordination mechanisms like steering committees working groups and clear escalation paths, planning cross functional rollouts and handoffs, tailoring messages and metrics to different audiences, and measuring cross functional outcomes while managing resistance during change.

MediumTechnical

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Data engineering resists producing a new dataset that falls outside existing pipelines. You need that data for model training but must respect their constraints. Propose a negotiation strategy and technical approach (sampling, derived datasets, side pipelines, temporary contracts) to obtain required data while minimizing operational burden on data engineering.

EasyTechnical

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Explain the difference between SLOs and SLAs in the context of AI services. Propose a set of SLOs for a recommender system on a high-traffic e-commerce site, including SLIs, targets, and recommended monitoring frequency and alerting behavior.

MediumTechnical

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Case study: You are coordinating with marketing to launch a generative AI feature that produces customer-facing content. Create a joint go-to-market checklist covering messaging, brand voice definitions, legal/compliance sign-off, support training, an internal beta, metrics to track post-launch, and contingency/rollback plans.

HardTechnical

0 practiced

As a senior AI Engineer charged with increasing AI adoption in an organization resistant to change, propose a multi-year change plan. Include short-term quick wins, identification and empowerment of change agents, incentive models, knowledge-transfer programs, measurement of adoption, and risk mitigation for failed pilots.

MediumTechnical

0 practiced

You need to facilitate a cross-functional workshop to define evaluation criteria for an ML model (business metrics, latency budgets, fairness constraints, and monitoring requirements). Describe the agenda, required participants, breakout activities, artifacts to produce, and how you will secure buy-in and owners for each criterion.

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