Senior Agentic AI Architect - European Economic Area - IBU

Deskripsi

We are seeking an experienced Senior AI Architect with a strong background in designing and delivering enterprise-grade AI and data-driven solutions. The ideal candidate will demonstrate clear career progression with increasing architectural ownership, technical leadership, and responsibility in complex AI initiatives.

This role requires deep hands-on expertise in Python and proven experience delivering AI systems into production environments — not just proof-of-concepts — including scalable, high-performance solutions for enterprise clients.

Key Responsibilities

Enterprise AI Architecture & Delivery

• Design and lead end-to-end architecture for enterprise AI solutions, ensuring scalability, performance, and reliability.
• Own AI solution architecture from data ingestion to model deployment and monitoring.
• Deliver production-grade AI systems using:
• PyTorch / TensorFlow
• Traditional ML frameworks such as XGBoost, LightGBM
• Architect AI systems for enterprise clients with high availability and compliance requirements.
• Ensure AI platforms are production-ready, secure, and performance-optimized.

Advanced AI Implementation (Hands-On)

• Build and deploy Agentic AI systems, RAG (Retrieval-Augmented Generation) architectures, and multi-agent frameworks in real-world environments.
• Design scalable RAG pipelines with vector databases and optimized retrieval strategies.
• Lead implementation beyond PoCs into fully operational enterprise systems.
• Drive architectural decisions around orchestration, memory, tool usage, and AI workflow design.

System Design & Technical Architecture

• Develop high-level and low-level architectural designs, system diagrams, and technical documentation.
• Design integration patterns across cloud platforms, APIs, data systems, and enterprise applications.
• Ensure robust system design covering:
• Scalability
• Fault tolerance
• Monitoring
• Observability
• Security
• Collaborate with cross-functional teams including Data Engineering, DevOps, Security, and Product.

Technical Leadership & Ownership

• Demonstrate platform-level ownership and decision-making authority.
• Mentor engineering teams and guide AI best practices.
• Lead architecture reviews and contribute to long-term AI platform strategy.
• Translate business requirements into scalable AI solutions.