AI Engineer: Multi-Agent LLM & RAG Solutions

GPTZero

United States

On-site

USD 150,000 - 250,000

Full time

14 days+

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Job summary

GPTZero is seeking an experienced software engineer to build the next generation of AI tools that preserve critical thinking and trusted AI interactions. You’ll fine-tune language models, craft prompts, and develop multi-agent workflows using RAG, collaborating with product and design to ship user-friendly, societally impactful software.

The ideal candidate has strong Python, hands-on with Langchain or LlamaIndex, and a track record of modular, extensible pipelines.

Qualifications

  • 3+ years of Python development experience.
  • 1+ year in LangChain or LlamaIndex.
  • 1+ year with agentic or RAG applications.
  • Strong exploratory data analysis (EDA) skills.
  • Experience advancing LLM capabilities on novel tasks.
  • Excellent, modular software engineering with extensible codebases.
  • Self-starter, able to own projects in a fast-paced team.
  • Willingness to wear multiple hats and lead as the team grows.
  • Visa for work in Canada or US.

Responsibilities

  • Fine-tune and evaluate state-of-the-art language models.
  • Optimize prompts to maximize classification accuracy, personalize outputs, and enforce style guidelines.
  • Develop multi-agent workflows incorporating data from diverse sources using RAG.
  • Improve AI agents with observability and experimentation tools.
  • Stay up-to-date with literature and emerging technologies to solve novel problems.
  • Work closely with product and design teams to develop intuitive applications that create societal impact.

Skills

Python
Langchain
LlamaIndex
RAG
EDA
Software engineering
Leadership
Communication

Tools

DsPY
TextGrad

Job description

GPTZero is seeking an experienced software engineer to build the next generation of AI tools that preserve critical thinking and trusted AI interactions. You’ll fine-tune language models, craft prompts, and develop multi-agent workflows using RAG, collaborating with product and design to ship user-friendly, societally impactful software.

The ideal candidate has strong Python, hands-on with Langchain or LlamaIndex, and a track record of modular, extensible pipelines.

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