Lead AI Architect, CH/UK/India/DE

Kandou seeks a Lead AI Architect to design and build advanced agentic AI systems, transitioning research concepts into production-ready applications with a focus on neuro-symbolic reasoning.

This position centers on developing agentic systems that extend far beyond standard conversational interfaces. The successful candidate will drive the transition from theoretical research to functional, real-world systems, handling complex analytical workflows and tool-using agents.

Responsibilities

• Architect and deploy practical agentic AI solutions utilizing contemporary orchestration tools and agent frameworks.
• Engineer sophisticated agentic workflows that perform complex analysis and interact with external tools, moving past simple chat interactions.
• Implement knowledge-centric AI structures, such as retrieval-augmented generation (RAG) and knowledge graph integrations.
• Establish controls for inference processes, including planning constraints, guardrails, and validation layers.
• Investigate and apply neuro-symbolic methodologies to enhance agentic reasoning capabilities.
• Construct transparent AI mechanisms that ensure agent behaviors are traceable and explainable.
• Design and maintain evaluation frameworks to test and benchmark agentic system performance.
• Develop full-stack prototypes and production-grade applications.
• Collaborate closely with researchers, engineers, product teams, and domain experts.
• Monitor and integrate the latest advancements in agentic AI and reasoning systems.

Requirements

• Proven experience with neuro-symbolic reasoning techniques.
• Strong background in developing real-world AI agents or agentic workflows across multiple projects.
• Demonstrated expertise in agentic reasoning, including planning, task decomposition, tool usage, and multi-step inference.
• Experience in either industrial AI development or academic research settings.
• Hands-on experience with knowledge-based agentic systems.
• Proficiency in methods for controlling reasoning or inference processes.
• Familiarity with neuro-symbolic AI concepts or hybrid reasoning architectures.
• Experience in designing transparent, inspectable, or explainable AI methods.
• Practical experience with agentic reasoning evaluation, testing, benchmarking, observability, or failure analysis.
• Full-stack web development experience, including backend APIs and frontend application development.

Nice to have

• Publications at major NLP/ML/AI conferences.

How to apply

Documents to submit:

• Portfolio
• Open-source contributions