AI Engineer

At Airbus, we are harnessing the power of artificial intelligence to enhance efficiency and quality across our value chain. Our team is composed of technologists and business leaders dedicated to innovation and excellence.

We are seeking a visionary, highly skilled, and innovative AI Engineer (4–7 Years) to join our high-impact team. In this role, you will architect, build, and deploy production-grade AI-driven products designed to automate complex engineering workflows, accelerate software transformation, and drive intelligent digital paradigms. You will turn ambiguous, cutting-edge AI concepts into scalable, reliable, cost effective and high-performing enterprise platforms.

Cloud Platform Mastery: Extensive expertise in Google Cloud Platform (GCP) , including Vertex AI, Cloud Run, BigQuery, Cloud Functions, and GKE.

Generative AI & LLM Frameworks: Strong proficiency in applying LLMs, RAG architectures, vector databases (e.g., Pinecone, ChromaDB, Vertex Vector Search), and frameworks like LangChain or LlamaIndex to build complex software automation tools.

Programming & Software Engineering: Mastery of Python and solid proficiency in modern web/backend stacks (RESTful APIs, gRPC, microservice design patterns, modern frontend frameworks).

Code Parsing & AST Analysis: Familiarity with abstract syntax trees (ASTs), static code analysis, compiler concepts, or domain-specific language (DSL) translation techniques.

MLOps & DevOps: Hands-on experience with MLOps workflows, model tracking, automated testing, containerization (Docker, Kubernetes), and CI/CD pipelines.

AI Cost Monitoring & FinOps: Proven experience in token metering, cost attribution, model routing policies (balancing frontier models vs. smaller open-source models for cost efficiency), and monitoring tools (OpenTelemetry, Cloud Monitoring).

Prior experience building source-to-source compilers, automated code conversion utilities, or automated design document generators.

Familiarity with software architecture patterns, legacy enterprise frameworks, and multi-language code conversion strategies.

Knowledge of quantitative product analytics to track AI feature adoption, model accuracy, and user efficiency improvements.

An active GitHub profile or portfolio demonstrating end-to-end AI applications, open-source contributions, or custom LLM tooling.

Product Efficiency & Impact: Quantifiable reduction in manual technical debt and turnaround time for automated code and document generation tasks.

System Scalability & Reliability: High uptime, low inference latency, and robust error handling across production AI pipelines on GCP.

Innovation & Quality: Successful deployment of high-accuracy AI models that consistently outperform baseline metrics in complex, domain-specific tasks.

Collaboration & Delivery Efficiency: Timely feature releases, clean API handoffs, low rework rates, and strong cross-functional alignment throughout the product lifecycle.

This job requires an awareness of any potential compliance risks and a commitment to act with integrity, as the foundation for the Company’s success, reputation and sustainable growth.

Company:

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Airbus is, and always has been, committed to equal opportunities for all. As such, we will never ask for any type of monetary exchange in the frame of a recruitment process. Any impersonation of Airbus to do so should be reported to emsom@airbus.com .

At Airbus, we support you to work, connect and collaborate more easily and flexibly. Wherever possible, we foster flexible working arrangements to stimulate innovative thinking.