Free Amazon AIP-C01 Exam Questions

Question 1

A large financial services enterprise is building a centralized platform to allow internal development teams to consume Foundation Models (FMs) from Amazon Bedrock. To ensure strict compliance and governance, the organization requires a "GenAI Gateway" architecture.The architecture must meet the following requirements:Prevent "Shadow AI" by forcing all internal applications to route requests through a single control point that logs every prompt and response for auditing.Automate the testing of prompt templates. Whenever a prompt engineer updates a standard system prompt, it must be automatically evaluated for toxicity and accuracy before being made available to applications.Ensure that PII is automatically redacted from prompts before they are sent to the model provider.Which combination of actions should you implement to achieve this?

A : Grant all internal application roles direct IAM permissions to bedrock:InvokeModel. Enable AWS CloudTrail data events for Amazon Bedrock to capture the request payloads and response bodies for auditing purposes.

B : Use Amazon Inspector within the CI/CD pipeline to scan the weights of the Amazon Bedrock base models for vulnerabilities and malware before approving them for use in the production environment.

C : Implement AWS AppSync with a direct data source to Amazon Bedrock. Use VTL resolvers to hardcode the system prompts within the API definition, ensuring that developers cannot modify them without redeploying the API.

D : Develop a centralized REST API using Amazon API Gateway and AWS Lambda. Configure the Lambda function to act as an abstraction layer that intercepts requests, uses Amazon Comprehend to detect and redact PII, logs the transaction to Amazon CloudWatch Logs, and then invokes Amazon Bedrock.

E : Create an AWS CodePipeline for prompt versioning. Include an AWS CodeBuild stage that runs an automated evaluation script (using a library like Ragas or specific Bedrock evaluations) against the new prompt candidate. Configure the pipeline to fail and rollback if the toxicity score exceeds a defined threshold.

Answer: D,E

Question 2

A healthcare company stores patient intake forms, insurance documents, and medical records as PDF files in multiple Amazon S3 buckets. Before building a GenAI document summarization system, the security team needs to identify which S3 buckets contain sensitive PII (like Social Security numbers, patient names, and medical record numbers) to ensure proper access controls are in place.Which AWS service should the security team use to automatically discover and classify sensitive data across their S3 buckets?

A : Amazon Inspector

B : Amazon Macie

C : Amazon Comprehend

D : AWS CloudTrail

Answer: B

Question 3

A financial services company uses Amazon Bedrock to generate investment analysis reports. The prompt engineering team frequently updates prompts to improve output quality, but recent production incidents showed that prompt changes caused incorrect financial calculations.The company requires a solution that enables prompt versioning with the ability to rollback to previous versions, tracks which prompt version generated each report for audit compliance, sends alerts when prompt performance degrades (measured by downstream validation failures), and maintains a complete audit trail of all prompt changes for regulatory reviews.Which solution meets ALL these requirements with the LEAST operational overhead?

A : Use Bedrock Prompt Management to create and version prompts. Store each prompt version with metadata tags indicating the version number. Configure CloudWatch Logs to capture all Bedrock InvokeModel requests with prompt details. Create a Lambda function that parses CloudWatch Logs, detects validation failures, and publishes alerts to SNS. Store prompt change history in DynamoDB for audit reports.

B : Use Bedrock Prompt Management to create versioned prompts with immutable versions and aliases. Tag each report with the prompt version/alias used during generation and log this to CloudWatch Logs. Enable CloudTrail to capture all Bedrock API calls including prompt updates. Create CloudWatch metric filters on validation failure logs and configure CloudWatch Alarms to trigger SNS notifications when failure rates exceed thresholds. Use CloudTrail Event History and CloudWatch Logs Insights for audit trail queries.

C : Store prompts as text files in S3 with version control enabled. Implement a Lambda-based prompt versioning system that reads prompts from S3, tracks versions in DynamoDB, and passes prompts to Bedrock InvokeModel API. Configure S3 Event Notifications to trigger Lambda functions that log prompt changes to CloudWatch. Use CloudWatch Synthetics to test prompt quality and send alerts via SNS when tests fail.

D : Use AWS Systems Manager Parameter Store to manage prompts with versioning enabled. Create a Step Functions workflow that retrieves the prompt version from Parameter Store, invokes Bedrock, and logs the prompt version and output to CloudWatch Logs. Enable Parameter Store change notifications via EventBridge to track prompt updates. Create CloudWatch Alarms based on custom metrics published by the Step Functions workflow when validation failures occur.

Answer: B

Question 4

A fintech company is launching a GenAI-powered "Spending Analyzer" feature. The application uses a Large Language Model (LLM) on Amazon Bedrock to explain transaction history to users. The project has two critical governance requirements:Compliance: The model must strictly refuse to answer any questions related to "Tax Advice" or "Legal Liability," as the company is not licensed to provide these services.Agility: The non-technical Product Team needs the ability to update the "Persona" and "Output Format" (e.g., switching from paragraphs to bullet points) of the analyzer weekly without requiring the engineering team to deploy new application code.Which combination of AWS GenAI features should the developer implement to meet these requirements? (Choose two)

A : Fine-tune the Foundation Model using Amazon SageMaker JumpStart on a dataset of "Refusal" examples. Train the model to recognize tax-related questions and output a standard disclaimer.

B : Implement Amazon Bedrock Prompt Management. Create a parameterized prompt template that defines the System Prompt (Persona) and output structure. Grant the Product Team permissions to iterate, test, and version the prompt within the Bedrock console.

C : Implement a post-processing AWS Lambda function. Use a keyword list (e.g., "tax", "audit", "lawyer") to scan the generated text. If a restricted keyword is found, overwrite the response with a hardcoded error message.

D : Use AWS Systems Manager Parameter Store to hold the System Prompt string. Update the backend Lambda function to fetch the latest prompt version on every invocation. Give the Product Team access to the Systems Manager console to edit the string.

E : Create an Amazon Bedrock Guardrail. Configure a "Denied Topics" policy that explicitly defines "Tax Advice" and "Legal Advice" with description examples. Attach this guardrail to the model invocation to intercept and block restricted queries.

Answer: B,E

Question 5

A financial services company uses an AI application to process financial documents by using AmazonBedrock. During business hours, the application handles approximately 10,000 requests each hour, whichrequires consistent throughput.The company uses the CreateProvisionedModelThroughput API to purchase provisioned throughput. AmazonCloudWatch metrics show that the provisioned capacity is unused while on-demand requests are beingthrottled. The company finds the following code in the application:response = bedrock_runtime.invoke_model(modelId="anthropic.claude-v2",body=json.dumps(payload))The company needs the application to use the provisioned throughput and to resolve the throttling issues.Which solution will meet these requirements?

A : Increase the number of model units (MUs) in the provisioned throughput configuration.

B : Replace the model ID parameter with the ARN of the provisioned model that theCreateProvisionedModelThroughput API returns.

C : Add exponential backoff retry logic to handle throttling exceptions during peak hours.

D : Modify the application to use the invokeModelWithResponseStream API instead of the invokeModelAPI.

Answer: B