What does an OpenAI on AWS developer do?
An OpenAI on AWS developer builds applications that call OpenAI models through Amazon Bedrock’s OpenAI-compatible APIs under strict AWS security controls. This role replaces direct connections to OpenAI servers with the bedrock-mantle endpoint to keep data within your AWS environment. The developer configures authentication, manages model IDs, and routes inference requests using standard OpenAI SDKs adapted for Bedrock.
- Integrate OpenAI model calls by replacing the standard base URL with the bedrock-mantle endpoint and using the /openai/v1/responses path. You write application code in Python or TypeScript that sends requests to this specific API route while maintaining compatibility with existing OpenAI libraries. This approach allows you to use familiar tools while leveraging AWS infrastructure for model access.
- Configure authentication and authorization by setting up Bedrock API keys or AWS credentials and applying precise IAM permissions. You define IAM policies that grant only the necessary access to bedrock-mantle inference actions and restrict other AWS resources. This setup ensures that only approved applications and users can trigger model calls within your account.
- Set up Codex workflows to route local CLI and IDE inference requests through Amazon Bedrock instead of public endpoints. You configure the Codex VS Code extension or CLI to use Bedrock credentials and point to the bedrock-mantle Responses API. This configuration lets developers use AI coding assistants while keeping all traffic and logs inside your AWS environment.
- Implement governance and observability by enabling AWS CloudTrail logging for all model calls made through the bedrock-mantle endpoint. You organize workloads using Amazon Bedrock Projects to isolate different teams or applications and apply separate access controls. This structure helps you monitor costs, track usage patterns, and maintain clear audit trails for compliance requirements.
- Select and manage specific OpenAI model IDs that correspond to the bedrock-mantle endpoint in your chosen AWS region. You verify that the model identifiers match the available options in Bedrock and adjust your application code to reference these exact IDs. This step ensures that your application calls the correct model version and avoids errors from unsupported or mismatched identifiers.
How to hire an OpenAI on AWS developer on Upwork
Step 1: Post a job
Define your need for a developer who routes OpenAI model calls through Amazon Bedrock. Use the Job Post Generator powered by Uma™, Upwork's Mindful AI to draft your post. Describe your requirements in a few sentences and Uma creates a tailored job description. You can write a new post, update a saved draft, or reuse an existing post.
- Specify that the freelancer must configure the bedrock-mantle endpoint to replace the standard OpenAI base URL.
- Request experience with AWS IAM policies to secure access to the OpenAI-compatible Responses API.
- Ask for examples of integrating Codex CLI or VS Code extensions with Amazon Bedrock credentials.
Step 2: Evaluate candidates
Look for portfolios that show working applications calling OpenAI models via Amazon Bedrock. Uma runs instant video interviews and builds shortlists with side-by-side comparisons to help you assess technical fit.
- Verify that their code samples use the correct Bedrock OpenAI model IDs for specific AWS regions.
- Check for configuration files that demonstrate proper authentication using Bedrock API keys or AWS credentials.
- Confirm they have set up AWS CloudTrail logging to track model inference calls for governance.
Step 3: Interview your top choices
Discuss how they handle workload isolation and cost monitoring within Amazon Bedrock Projects. Schedule these conversations within Upwork Messages to receive an immediate transcript and summary after each session.
- Ask how they structure Requests via the /openai/v1/responses path to support multi-turn state.
- Question their approach to managing AWS permissions for Bedrock Mantle inference access.
- Explore their method for routing local IDE workflows through the Bedrock-backed Responses API.
Step 4: Agree on scope and begin work
Set clear milestones for building application code that integrates with the bedrock-mantle endpoint. Use Upwork Messages and the contract workroom for communication while identity verification and Hourly Payment Protection secure your project funds.
- Require delivery of configured SDK clients that authenticate correctly with AWS credentials.
- Mandate setup of Bedrock Projects to enforce access control and isolate specific workloads.
- Include testing of Codex configurations to ensure inference routes through Bedrock without errors.
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