Senior AI Architect (w/m/x)

Responsibilities

• AI Architecture and Solution Design
  • Define end-to-end architecture for AI and GenAI solutions, including classical ML, NLP, multimodal AI, and agentic systems.
  • Design scalable and secure architectures for LLM-based applications, Retrieval-Augmented Generation (RAG), Agentic and multi‑agent systems, and multimodal solutions such as image-to-text, video understanding, and speech-to-text.
  • Translate business requirements into technical solution designs, architectural blueprints, and implementation roadmaps.
  • Ensure AI solutions are aligned with enterprise architecture, cybersecurity, data governance, and compliance requirements.
• Delivery Leadership
  • Lead AI solution development across the full lifecycle: discovery, requirements gathering, experimentation, prototyping, testing, deployment, and production support.
  • Partner with cross‑functional teams to industrialize AI use cases and transition prototypes into scalable enterprise products.
  • Drive best practices in AI engineering, reusable components, and platform‑based delivery.
  • Support project planning, estimation, prioritization, and technical risk management.
• Technical Leadership
  • Provide technical leadership to multidisciplinary teams including data scientists, ML engineers, data engineers, analysts, and software developers.
  • Mentor team members and help grow organizational capability in AI architecture, GenAI, MLOps, and responsible AI.
  • Review solution designs, code, model approaches, and deployment strategies to ensure quality and maintainability.
  • Contribute to technical standards, architecture governance, and design reviews.
• Stakeholder Engagement
  • Engage with business and functional leaders to identify AI opportunities and define high‑value use cases.
  • Present technical concepts and solution proposals to senior stakeholders in a clear and business‑relevant way.
  • Support pre‑sales, RFI/RFP responses, capability presentations, and client/internal leadership discussions where applicable.
  • Act as a trusted advisor on AI strategy, feasibility, scalability, and adoption.
• Operational Excellence and Responsible AI
  • Define and promote best practices for model deployment, monitoring, MLOps, observability, versioning, and lifecycle management.
  • Ensure AI solutions are reliable, explainable where needed, and governed appropriately.
  • Promote secure, sustainable, and responsible use of AI technologies across the organization.
  • Stay current with emerging AI technologies and evaluate their relevance to business needs.

Required Skills and Experience

• Degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Mathematics, Statistics, or a related field.
• Proven experience designing and delivering AI solutions in production environments at scale.
• Experience working across multiple phases of the AI lifecycle, from ideation to production deployment.
• Generative AI expertise, including LLM application architecture, agentic workflows / multi‑agent systems, prompt design, and LLM orchestration.
• Experience with cloud‑based AI/ML ecosystems such as Azure, AWS, or GCP.
• Experience with data pipelines, API‑based integrations, and production‑grade AI systems.
• Understanding of solution architecture principles, including scalability, resilience, modularity, and security.

Benefits

Join us to see your career take flight today. We offer:

• Flexible work schedule and hybrid work model adjusted to your needs
• Fascinating job in dynamically growing aerospace industry
• Competitive salary, annual bonus, copyright costs tax reduction
• Diverse career opportunities globally
• Environment of continuous learning and improvement
• Onboarding support to make your start easier, mentoring support through your career
• Benefits fit to all lifestyles
• Wide variety of employee initiatives

Additional Information

Relocation Assistance Provided: No.