Freedom

Generative AI Integration Practitioner

Freedom

contract

Posted on:

Location Type: Remote

Location: United States

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About the role

  • Complete a practitioner-level skills assessment used for validation and standard-setting purposes.
  • Complete a short post-assessment survey providing feedback on the assessment experience.

Requirements

  • The candidate should be a current practitioner with applied, real-world experience related to the following knowledge areas and skills:
  • Integrate AI-powered code generation and completion tools into software development workflows
  • Evaluate and select appropriate generative AI tools for development tasks
  • Apply generative AI to automate and enhance code testing and quality assurance processes
  • Use generative AI to generate and maintain software documentation
  • Implement prompt engineering techniques to optimize AI-assisted development output
  • Understand the architecture and capabilities of large language models (LLMs) used in developer tools
  • Integrate AI-powered APIs and SDKs into existing applications
  • Apply best practices for security and data privacy when using generative AI in production code
  • Use generative AI tools for debugging, refactoring, and code review
  • Evaluate AI-generated code for correctness, efficiency, and maintainability
  • Understand the limitations and potential biases of generative AI in software development
  • Implement CI/CD pipeline integrations with AI-assisted tooling
  • Apply generative AI to design patterns, architecture decisions, and technical documentation
  • Manage AI model versioning and deployment in development environments
  • Active practitioner with hands-on experience in Generative AI Integration for Developers or closely related domains.
  • Practical, working knowledge of how the concepts listed above are applied in real professional settings.
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI-powered code generationgenerative AI toolscode testingquality assuranceprompt engineeringlarge language modelsAI-powered APIsdebuggingrefactoringCI/CD pipeline integrations
Soft Skills
practitioner-level skills assessmentfeedback provisionreal-world experiencehands-on experiencebest practices application