AWS Certified Generative AI Developer - Professional (AIP-C01) Practice Exam

A software company is deploying a code-generation assistant that uses a customized foundation model and a proprietary GPU inference container on Amazon SageMaker AI. The container supports incremental token generation. Load testing shows that, with sufficient capacity, the model produces its first token within 1 second and completes a response in 18–25 seconds. The application must display generated text within 2 seconds of a request and continue displaying tokens as they arrive. Two GPU instances can handle normal traffic, but scheduled customer training sessions immediately increase demand to a level that requires 20 instances. Additional instances take approximately 8 minutes to become ready. The company wants to minimize GPU costs outside the scheduled sessions without violating the interactive response requirement during those sessions. Which architecture best meets these requirements?

A logistics company uses a generative AI agent to propose customs classifications and supporting explanations for imported products. Before a classification is submitted, two trade specialists independently review the proposal through an Amazon Augmented AI (Amazon A2I) custom task. Each specialist can accept the proposal or provide a corrected classification. If the specialists select different classifications, a senior specialist must examine both responses and make the final selection. Neither a model-generated tie-breaker nor a default classification is permitted. Reviews can take several days. Failed or expired reviews must leave the shipment unsubmitted. The company uses AWS Step Functions Standard Workflows for orchestration and wants to retain the individual reviewer responses for auditing. Which implementation meets these requirements?

A financial services company uses Amazon Bedrock to generate structured investment recommendations. Company policy requires every recommended product to be approved for the customer's jurisdiction and every response to contain the current jurisdiction-specific disclosure. Jurisdiction is obtained from the customer's authenticated profile, and an authoritative policy service maintains approved products and disclosure text. These rules change independently of application deployments. All customer responses pass through a backend that currently streams model output. The company needs automated, auditable enforcement of these requirements before customers receive recommendations. Which solution BEST meets these requirements?

A product-catalog application uses Amazon Bedrock to generate a single JSON object containing product attributes and nested arrays of variant objects. The receiving system requires exactly one schema-valid JSON object and does not permit wrapper text or application-specific delimiters. Complete responses require between 300 and 1,800 output tokens. To avoid paying for commentary after the JSON, the developer configured stopSequences as ["}", "]"] and set the maximum output to 2,400 tokens. Production responses frequently end inside the first variant object, causing validation failures and additional model invocations. The inference responses indicate that a configured stop sequence was matched. The selected model supports native schema-constrained JSON output for the catalog's schema. The developer must reduce failed-response retries, preserve all required nested data, and prevent non-JSON commentary without changing the receiving system's format. Which change BEST meets these requirements?

A logistics company uses deterministic rules and manual review to extract shipment details from documents. The current process costs $630,000 annually, including review labor and losses from extraction errors. A developer evaluates four replacement configurations that use foundation models through Amazon Bedrock. Testing uses the same representative document set and projected production volume. All configurations meet mandatory accuracy, safety, and latency requirements. The evaluation produces the following cost estimates, in thousands of dollars. Setup costs are incurred once at deployment. All other costs cover a full year of production operation. Review-labor reductions represent actual reductions in contractor spending. Error losses are additional costs and are not included in review labor. | Configuration | One-time setup | Annual inference and operations | Annual review labor | Annual expected error losses | |---|---:|---:|---:|---:| | Economy model | 30 | 48 | 420 | 90 | | Premium model | 90 | 120 | 240 | 24 | | Rules-plus-model hybrid | 30 | 84 | 270 | 30 | | Customized model | 180 | 60 | 180 | 36 | The company wants the largest expected net financial benefit relative to the current process during the first 12 months after deployment. There are no other material costs or benefits, and the company does not assign value to benefits after this period. Which recommendation should the developer make?