AI Principal Architect | Frankfurt

Role - Senior Principal Technology Architect
Technology - GenAI, LLM,RAG,Agentic AI, AI workflows
Location - Frankfurt, Germany
Business Unit - GERENG
Compensation - Competitive (including bonus)

Job Description
The AI Principal Architect will lead the design and implementation of AI-driven product capabilities across multiple domains like Aero, Manufacturing, Retail, Finance etc using both Traditional & Generative AI + Machine Learning.
The role involves defining architecture, guiding development, and enabling innovation across AI/ML, LLM, RAG, and Agentic AI use cases. The ideal candidate combines strong technical depth with product mindset, collaboration, and leadership. The candidate should have technical consulting capabilities, Solutioning acumen, Domain knowledge on any of the industries where GEN AI is applied. Candidate should be able to conduct value stream workshops in discovering the AI implementation scope and able to create architecture and detailed solutions. Candidate should have excellent communication skills.

Key Responsibilities:

• Architect and deliver scalable GenAI solutions across data, model, and application layers.
• Define reference architectures, reusable patterns, and best practices for AI integration into products.
• Design and operationalize LLM, RAG, Copilot, and Agentic AI workflows.
• Familiarity with ML and able to integrate AI/ML solutions
• Establish MLOps and GenAIOps pipelines for model lifecycle management, monitoring, and governance.
• Collaborate with product, data, and engineering teams to translate business needs into AI-enabled features.
• Lead PoCs and innovation initiatives to evaluate emerging frameworks and technologies.
• Mentor teams on AI engineering, prompt design, and scalable deployment practices.
• Support pre-sales and customer discussions to define solution approaches and architecture options.
• Familiarity of a Product development Value chain in a domain.

• Strong foundation in NLP, and LLM-based architectures.
• Familiarity with machine learning, deep learning ( Strong knowledge is an added advantage )
• Hands-on expertise with Python, TensorFlow, PyTorch, LangChain, LangGraph/CrewAI/AutoGen, Hugging Face, and MLflow.
• Experience with cloud AI ecosystems - AWS (SageMaker, Bedrock), Azure (AI Studio, OpenAI), or GCP (Vertex AI). GraphRAG
• Experience in Foundation models , Codex tool plugins, New Coding tools ( Cursor, Devin )
• Knowledge of vector databases (e.g., Pinecone, Weaviate, FAISS, MILVUS ) and RAG pipelines.
• Familiarity with containerization (Docker, Kubernetes) and MLOps workflows.
• Exposure to prompt engineering, fine-tuning, evaluation, and responsible AI practices.
• Understanding of data engineering, model observability, and AI governance.

• Strong analytical, problem-solving, and communication abilities.
• Collaborative mindset with ability to work across product, engineering, and data teams.
• Thought leadership in driving AI adoption, innovation, and best practices.
• Experience supporting AI CoE initiatives and customer engagements.