Job Description:
Focus: Use off-the-shelf LLMs for code generation, test generation, and code validation. Requires a basic understanding of Go and Python.
Tools: ChatGPT, Gemini, Copilot, etc.
2+ years of experience working with LLMs or NLP systems (e.g., GPT, Claude, LLaMA).
Strong understanding of prompt engineering techniques, including few-shot, zero-shot, and chain-of-thought prompting.
Familiarity with aerospace systems, terminology, and documentation standards (e.g., ARP4754A, DO-178C).
Proficiency in Python or similar scripting languages for AI model interaction.
Design, test, and optimize prompts for AI models used in aerospace engineering, documentation, diagnostics, and training systems.
Collaborate with software engineers, data scientists, and domain experts to align AI outputs with aerospace standards and safety requirements.
Analyze AI model behavior and performance to refine prompt strategies and improve accuracy, reliability, and contextual relevance.
Develop prompt libraries and templates for use across Safran's AI platforms.
Ensure compliance with ethical AI practices, data privacy, and aerospace regulatory standards.
Support the integration of AI tools into digital twin systems, predictive maintenance platforms, and engineering knowledge bases.
Document prompt engineering methodologies and contribute to internal training materials.