• 1 to 3 years of software engineering experience (or equivalent), with strong fundamentals.
• Proficiency in Python and/or TypeScript and comfort with SQL.
• A real understanding of how modern AI systems work under the hood: LLMs and prompting, tokens and context windows, embeddings and vector search, RAG, and basic evaluation of model output.
• Genuine interest in applied AI and a desire to go deep on the domain.
• Strong ownership and comfort in a fast-moving environment.
• Hands-on experience with LLM orchestration and RAG tooling (for example LangChain, LlamaIndex, or similar) and vector databases (for example pgvector, Pinecone, or Weaviate).
• Experience building agents, tool/function calling, or evaluation and prompt-testing pipelines.
• Experience with React, Postgres, or cloud platforms, or with document-heavy data.