Job Description

About Base0

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Base0 is building the future of context-aware AI. At the heart of our platform is the Intelligence Layer--a system that captures, organizes, and reuses project knowledge across tools to deliver precise, context-rich outputs wherever you work.


We're solving one of the biggest challenges in modern AI workflows: fragmented context. Today, project knowledge is scattered across chats, prompts, and tools--forcing teams to spend more time steering AI than actually getting work done. Base0 brings context, continuity, and observability to AI-powered work, enabling AI-native teams to ship faster, work smarter, and maximize productivity.


We're a fast-moving, venture-backed team with a proven track record of building and scaling successful AI companies. Freshly funded and growing, we're looking for builders who want to help define the next frontier of human-AI collaboration.

Role Summary

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You'll own the systems behind Base0's Intelligence Layer--building the pipelines, retrieval systems, and evaluations that transform AI memory into contextual understanding.


This means experimenting with how to extract, represent, and retrieve knowledge from thousands of conversations--and turning those experiments into working systems that power real user experiences across our API and user-facing features/products.


If you're excited by turning product ideas into working LLM systems and iterating through research, data, and prototypes to find what works, you'll thrive here.

What You'll Build

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

Skills We're Looking For

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Strong

Python engineering fundamentals

--comfortable designing and shipping data or model pipelines end-to-end. 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. Exposure to

fine-tuning or adapter training

(LoRA, PEFT) and how to integrate tuned models into retrieval pipelines. Ability to work

end-to-end

--backend (FastAPI, Node) 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.

If you thrive on autonomy, clarity, and collaboration and want to build the connective tissue between humans and AI systems, Base0 is where you'll do your best work.