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AI Agent Memory Persistence Engineer

Stella Tran

Full-time · Job · Amsterdam

About the role

LangChain, vector stores, and long-running agent loops are the core of what we build. If you've ever watched an agent forget a decision it made three turns ago, you already understand the problem this role solves. You will design the memory persistence layer that lets our multi-agent framework retain relevant context across sessions, days, and even agent restarts, without ballooning token costs on every call. You'll ship this as a first-class part of our open framework, working closely with the orchestration team that owns agent routing and the context-compression research already in production.

Responsibilities

  • Design a persistence layer allowing agents to retain context across sessions and restarts
  • Build retrieval strategies that surface relevant memories without inflating token usage
  • Integrate persistence primitives into our existing multi-agent orchestration framework
  • Benchmark memory retrieval quality against long-horizon task completion rates
  • Contribute design docs and examples to our open-source framework documentation

Requirements

  • 5+ years building production LLM systems, ideally agent frameworks
  • Deep hands-on experience with LangChain or similar orchestration tooling
  • Strong Python skills and comfort with containerized services
  • Experience with vector stores and retrieval-augmented architectures

Benefits

  • Fully remote, distributed team across nine time zones
  • Competitive salary and equity
  • Open-source contributions count toward performance reviews
  • Home office and co-working stipend

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Categories

MLOps & AI Infrastructure NLP & Prompt Engineering

Skills

python langchain openai api docker

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

MLOps & AI Infrastructure NLP & Prompt Engineering

Skills

python langchain openai api docker

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