GenAI Engineer

You should be someone who likes to solve a problem on paper before opening an AI coding tool. AI should make you faster, but the thinking and decision-making must still come from you.

You should understand the difference between:

• A process that needs straightforward automation
• A task that benefits from an AI-powered application
• A problem that genuinely requires an AI agent

You should also be comfortable with workflow builders and understand practical best practices such as branching, retries, error handling, logging, human approval steps, tool permissions and fallback paths.

We expect an intermediate-level understanding of concepts such as:

• Vector databases and vector storage
• Embeddings and similarity search
• Chunking strategies
• Retrieval-Augmented Generation, or RAG
• Horizontal and vertical scaling or distribution
• Linear algorithms and basic algorithmic thinking
• Context management, evaluation and hallucination control
• Tool calling and multi-step agent workflows

You do not need to know every term academically. However, you should be able to explain where these concepts are useful, what trade-offs they involve and how you have applied them while building something.