AI Engineer – Generative AI & Cloud Platform

About the role

Airbus is building AI‑driven products to automate complex engineering workflows and accelerate software transformation. The AI Engineer will design, develop, and deploy production‑grade AI solutions that modernize legacy codebases and technical documentation.

Key responsibilities

• Lead end‑to‑end AI product engineering, from architecture and model selection to production deployment and performance monitoring.
• Design intelligent automation systems using NLP and large language models to parse, translate, and modernize complex legacy code.
• Develop prompt engineering, retrieval‑augmented generation pipelines, and fine‑tuned models for domain‑specific artifact generation.
• Build scalable AI micro‑services on Google Cloud Platform, leveraging serverless architectures and batch processing pipelines.
• Collaborate with product managers, UX designers, and software architects to ensure seamless integration into enterprise ecosystems.

Required profile

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related quantitative field.
• 4–7 years of hands‑on experience building, deploying, and scaling AI/ML products, including generative AI applications.
• At least one recognized cloud or AI certification (e.g., Google Cloud Professional Machine Learning Engineer).

Required skills

• Google Cloud Platform expertise (Vertex AI, Cloud Run, BigQuery, Cloud Functions, GKE).
• Generative AI and LLM frameworks (RAG, vector databases such as Pinecone, ChromaDB, Vertex Vector Search, LangChain, LlamaIndex).
• Strong Python programming and experience with RESTful APIs, gRPC, and microservice design.
• Knowledge of code parsing, abstract syntax trees (AST), and static analysis techniques.
• MLOps and DevOps skills (Docker, Kubernetes, CI/CD pipelines, model tracking).
• AI cost monitoring and FinOps practices (token metering, OpenTelemetry, cost attribution).