Free Amazon AIP-C01 Exam Questions

Question 1

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 2

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 3

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 4

A media company is building a content recommendation engine that uses Amazon Bedrock embeddings to find similar articles based on semantic meaning. They need a fully managed vector database that can efficiently perform k-nearest neighbor (k-NN) searches across millions of article embeddings. The team wants a service that integrates natively with their existing search infrastructure and supports both keyword and vector search.Which AWS service should the team use as their vector database?

A : Amazon ElastiCache

B : Amazon DynamoDB

C : Amazon RDS PostgreSQL

D : Amazon OpenSearch Service

Answer: D

Question 5

A manufacturing company uses a legacy on-premises ERP system to track assembly line issues. The company wants to integrate Amazon Bedrock to automatically analyze "Technician Notes" (unstructured text) and categorize the root cause of failures using the Anthropic Claude 4.5 Sonnet model.The legacy ERP system has a strict limitation: it blocks all user operations while waiting for external API responses and times out if a response takes longer than 300 milliseconds. The GenAI analysis typically takes 3–5 seconds to complete.As a GenAI Developer, which integration architecture should you design to incorporate the Foundation Model (FM) capabilities without disrupting the legacy system's operations?

A : Use AWS AppSync with a GraphQL subscription. configure the ERP system to subscribe to the RootCauseAnalysis mutation. When a note is saved, trigger the mutation to invoke Amazon Bedrock directly. The subscription connection keeps the channel open without blocking the main ERP thread, allowing the response to stream back when ready.

B : Create an Amazon API Gateway REST API with a synchronous integration to an AWS Lambda function. Configure the ERP to call this API with the notes. Update the Lambda function to increase the memory allocation to 10 GB, ensuring the model inference completes within the 300-millisecond window.

C : Implement an asynchronous, event-driven architecture. Configure the ERP to push the technician notes to an Amazon SQS queue and immediately return success to the user. Use an AWS Lambda function to poll the queue, invoke the Amazon Bedrock model for analysis, and write the classification results back to the ERP database via a separate callback API.

D : Deploy an AWS PrivateLink connection between the on-premises network and the Amazon Bedrock service endpoint. Configure the ERP system to make direct HTTPS calls to the Bedrock InvokeModel API using the private endpoint, bypassing the public internet to reduce network latency below the 300-millisecond threshold.

Answer: C