Job Description:

At Airbus Defence and Space, we are dedicated to pushing the boundaries of innovation in the aerospace industry.

Our DAISEI project is a cutting-edge collection of browser-based and API Artificial Intelligence Services, enabling seamless interaction with AI models and services across the intranet.

We are seeking a dynamic and experienced Lead DevOps Engineer to join our team within Airbus Defence and Space in Toulouse (Palays site), and drive the operational excellence of our products in both cloud and on-prem environments under strict security constraints.

Job Summary:

We are seeking a passionate and skilled Lead DevOps Engineer to oversee and actively participate in the deployment, operation, and maintenance of our software products, with a focus on AI/ML and Generative AI/LLM models.

In this role, you will facilitate the continuous integration and delivery of our AI services, ensure adherence to standards, and validate technical solutions.

You will be responsible for improving the efficiency, reliability, and quality of our products, managing necessary improvements, and contributing to our Communities of Practice.

Your expertise in cloud (e.g. AWS managed services such as Sagemaker, EKS or RDS) as well as on-prem (OpenShift, Docker or Podman) technologies, as well as your ability to navigate complex security constraints, will be crucial to ensuring our national and European sovereignty.

Key Responsibilities:

• Define the Technical Roadmap: Define and own the long-term technical roadmap for the DAISEI platform's operational stack, ensuring architectural patterns support national/European sovereignty, extreme scalability, prepare the BROMO platform integration and multi-year growth.

• Architectural Governance: Establish, document, and govern the core DevOps and MLOps architectural patterns (IaC, CI/CD, Observability) that scale across the entire project/business unit, ensuring alignment with central enterprise standards.

• Strategic Technology Evaluation: Lead proof-of-concepts (PoCs) and perform deep technical evaluations of emerging cloud and on-prem technologies (e.g., new container orchestration solutions, serverless AI runtimes, advanced security tooling) for strategic adoption.

• Drive Architectural Definition: Drive the architectural definition of the product deployment and operation lifecycle. Define the standards for CI/CD pipelines and Infrastructure as Code (IaC) for both cloud and on-prem environments, ensuring their long-term viability and security.

• Cross-Team Technical Leadership: Serve as the primary technical point of contact and subject matter expert for DevOps principles, actively driving cross-functional alignment and standards with Development, AI/ML Science, and Cyber Security teams. Represent the organization as a technical expert in internal Communities of Practice and external forums, influencing best practices for secure, sovereign, and scalable AI infrastructure.

• Incident Management Strategy: Design and continually refine the high-level Major Incident Management and Disaster Recovery (DR) strategy, ensuring system resilience targets (RTO/RPO) are met and validated through regular drills.

• Cost and Resource Optimization: Drive strategic initiatives to optimize cloud and on-prem resource consumption (FinOps/Cost Governance), translating technical metrics into business value and efficiency.

• Technical Delegation & Coaching: Act as a hands-on contributor while effectively delegating implementation work to the DevOps Engineers, focusing your efforts on the highest-leverage architectural and governance challenges.

• Mentorship and Standards: Establish technical standards and governance for infrastructure and platform code. Mentor and coach DevOps Engineers in advanced systems architecture, reliability engineering, and security best practices.

What We Offer:

• The opportunity to work on cutting-edge projects and technologies in the aerospace industry, with a focus on AI/ML and Generative AI/LLM models, and a strong commitment to security and sovereignty.

• A collaborative and innovative work environment that encourages professional growth and development, and values and upholds our security and sovereignty requirements.

• Competitive salary and benefits package.

• The chance to make a real impact on the future of Airbus Defence and Space, and to contribute to the security and sovereignty of our national and European digital landscape.

Join Us:
If you are a passionate and experienced Lead DevOps Engineer looking for an exciting opportunity to drive operational innovation in the aerospace industry, particularly in the context of AI/ML and Generative AI/LLM models, and with a strong commitment to security and sovereignty, we would love to hear from you!

Apply now to join our dynamic team and contribute to the success of the DAISEI project.

Airbus Defence and Space is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, while upholding the highest standards of security and sovereignty.

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:

Airbus Defence and Space SAS

Employment Type:

Permanent

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Classe Emploi (France): Classe G13

Experience Level:

Professional

Job Family:

Digital <JF-IM-DI>

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Airbus is committed to achieving workforce diversity and creating an inclusive working environment. We welcome all applications irrespective of social and cultural background, age, gender, disability, sexual orientation or religious belief.

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.