AI Solution Architect

Long-term collaboration with an international, top-tier consulting firm providing IT services for large and mid-sized companies across sectors such as automotive, healthcare, finance, banking, and manufacturing.

• At least 10 years of overall IT experience.
• Minimum 3 years of experience in designing or engineering AI-based systems, including LLM-based applications, retrieval-augmented generation (RAG), vector databases, agentic workflows, and Python-based AI stacks (e.g., LangChain, LangGraph).
• Ability to design flexible and modular architectures rather than monolithic products.
• Experience in reviewing and validating multi-component solutions (data ingestion, ETL, AI layer, UI/UX where applicable).
• Strong problem-solving mindset and the ability to quickly propose pragmatic solutions.
• Comfort working across time zones, collaborating with architects and partners in the US, including availability for meetings and occasional work after 5:00 PM CET.
• Curiosity, collaboration skills, and willingness to share knowledge within a community of practice.
• Ability to support multiple teams simultaneously while maintaining high and consistent quality.
• Strong technical credibility and the ability to constructively challenge solutions and guide development teams.
• English proficiency at B2 or C1 level, enabling fluent communication in an international environment.

• Designing end-to-end architectures for GenAI/LLM solutions across more than 100 use cases.
• Reviewing requirements and business architecture documents and translating them into concrete, implementable solution designs.
• Close collaboration with TPMs and engineering teams to support implementation, identify risks, and ensure consistency of solutions.
• Creating scalable and reusable architectural patterns that enable component reuse across teams and industries (e.g., reusable agents for release management in SAP / Oracle / Guidewire environments).
• Balancing speed of delivery with process formalization at an early stage, while contributing to future standardization of solutions.
• Supporting the planning of multi-phase implementations and participating in feasibility assessments (POC, MVP).
• Participation in an architecture guild/committee as standards mature.