Base0 is looking for an Applied AI Engineer to own the systems behind our Intelligence Layer. You will be responsible for building the core infrastructure that extracts, represents, and retrieves knowledge from thousands of AI conversations, turning experiments into systems that power real user experiences.

What You'll Do

Build core AI systems that extract and organize knowledge from AI conversations into structured, reusable context.
Develop retrieval and memory infrastructure (GraphRAG + vector search) that delivers precise, low-latency context to user workflows.
Build agentic systems that reason across stored context, handling retrieval, synthesis, and evaluation tasks autonomously.
Create prompt and orchestration frameworks that connect multiple models, tools, and data sources into end-to-end reasoning pipelines.
Build evaluation and telemetry systems to benchmark retrieval quality, latency, and overall intelligence performance.
Develop fast prototypes to explore new product directions and validate user-facing capabilities.

What We're Looking For

Strong Python engineering fundamentals, skilled in building performant, maintainable systems and services that connect data, models, and APIs.
Deep understanding of retrieval architectures: embeddings, vector databases, hybrid or graph-based search, and caching strategies.
Experience with LLM orchestration frameworks like LangChain, LlamaIndex, or custom-built agent systems.
Proven ability to build and tune LLM-based agents for reasoning, synthesis, or evaluation tasks.
Familiarity with prompt engineering and multi-step reasoning, designing structured flows that balance quality, latency, and cost.
Ability to work end-to-end, from backend (FastAPI, Node.js) to quick front-end demos or dashboards for testing and iteration.
Comfort operating in open-ended problem spaces, defining your own experiments, and driving them to working outcomes.