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Confidential company

Job listing

San Francisco, United StatesNot Disclosed

Applied AI Engineer at Well-funded AI infrastructure startup

Are you ready to build the long-term memory layer for AI agents? We are looking for an Applied AI Engineer to own the 0 to 1 journey, turning complex customer needs into functional proofs-of-concept. Based in San Francisco, you'll join a high-velocity team backed by top-tier VCs to experiment with the latest LLM/RAG stacks. If you thrive on rapid prototyping, full-stack fluency, and extreme ownership in an office-first environment, this is your chance to shape how AI remembers and learns from every interaction.

Overview

Role overview

As an Applied AI Engineer, you will own the 0→1 journey by turning vague customer use cases into working proofs-of-concept. You will aggressively experiment with memory retrieval, build rapid full-stack prototypes, and partner with Research to implement cutting-edge techniques. This role is critical for showcasing how AI agents can leverage long-term memory effectively.

Company

About the company

Well-funded AI infrastructure startup

Responsibilities

What you will do

  • Build end-to-end proofs-of-concept (UI + APIs + data) that integrate AI memory into customer flows.
  • Experiment with embeddings, indexing, and hybrid search to optimize task-level quality and latency.
  • Collaborate with Research and Backend teams to prototype and hand off winning AI models and docs.

Candidate profile

Who this is a fit for

  • Full-stack fluency with Next.js/React and Python (FastAPI/Django) for rapid prototyping and deployment.
  • Hands-on experience with the LLM/RAG stack, including vector databases, retrieval strategies, and prompt engineering.
  • Proven track record of moving from idea to demo in days while maintaining high craftsmanship standards.

What makes it remarkable

Why this role is remarkable

  • Work at the forefront of AI agent technology by building the industry's long-term memory layer.
  • Backed by top-tier VCs and well-capitalized to solve complex challenges in the LLM/RAG stack.
  • Join an office-first culture in San Francisco that prioritizes velocity, craftsmanship, and extreme ownership.

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