Applied AI Engineer for Spartan, building production features with elite startup founders. Designing prompt templates, memory systems, and integrations in AI-driven solutions.
Responsibilities
Design clear prompt templates and role scaffolds (System/User/Assistant).
Keep chats relevant with windowing/summarization and retrieval-backed long-term memory; basic tenant/privacy scoping.
Chunk/clean docs, embed into a vector store, run hybrid retrieval (BM25 + dense), and return answers with citations.
Favor evidence, cite sources, and abstain when unsure.
Implement Plan → Act → Observe → Iterate; call APIs/DBs via typed tool contracts.
Requirements
Fluent in English — you’ll talk directly with US startup founders.
1+ years building production features (AI, search, or backend).
We’re language-agnostic.
Solid grasp of LLM fundamentals : chat vs completion, roles, tokens/context, structured prompts.
Hands-on with vector retrieval concepts (BM25, embeddings, HNSW/IVF) and basic grounding (citations/abstention).
Comfortable integrating external/internal tools via function-calling or typed contracts.
Strong CS fundamentals and a builder’s mindset — you own problems end-to-end.
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