Interview questions
Interviewing at Riverflex
Riverflex is an Amsterdam-based digital consultancy focused on building lean, scalable, and human-centered digital products that drive business transformation across industries. The company emphasizes AI integration including LLMs and agentic workflows, modern web frameworks, and cloud platforms, operating with a hybrid work model and strong engineering collaboration.
Can you quickly walk me through a recent project where you took ownership from concept to production, and what made your contribution unique to its success?
AI Full-Stack Product Engineer (Mid-Level)
Tell me about how you architected AgentNorth, focusing on persistent agent memory and auditability. What were the hardest technical problems, and how did you solve them?
AI Full-Stack Product Engineer (Mid-Level)
How have you delivered agentic workflows or multi-step LLM pipelines into production? Give a concrete example and walk through error handling and tool chaining.
AI Full-Stack Product Engineer (Mid-Level)
Describe how you’ve integrated real-time AI/ML fraud detection in a banking product, highlighting architecture and security controls.
AI Full-Stack Product Engineer (Mid-Level)
You have worked with Docker, Kubernetes, and AWS. Can you describe a production deployment pipeline you owned and any CI/CD improvements you spearheaded?
AI Full-Stack Product Engineer (Mid-Level)
Design a multi-tenant SaaS where each client’s data is isolated and custom features can be rolled out per client. What patterns and tools would you use?
AI Full-Stack Product Engineer (Mid-Level)
Have you worked directly with Azure or Databricks for cloud deployments? If not, how would you ramp up and connect your AWS experience?
AI Full-Stack Product Engineer (Mid-Level)
How do you ensure secure, compliant integration with third-party APIs in financial or SaaS products?
AI Full-Stack Product Engineer (Mid-Level)
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