Remote AI Engineer — LLM Tools & Workflow Architect

SavvyMoney, Inc.

United States

On-site

USD 90,000 - 150,000

Full time

14 days+

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Job summary

SavvyMoney, Inc. is seeking a full-time AI Engineer to design and deploy AI-powered workflow tools for diverse business teams. You will gather requirements directly from users, perform UAT, and define reference architectures for AI integration while working remotely across the organization.

The role emphasizes hands-on AI/ML experience, Python and AWS backend development, and collaboration with non-engineering teams to deliver internal tooling that scales with business needs.

Qualifications

  • 1-2+ years of professional software engineering experience, with at least 1 year in AI/ML or LLM-driven applications.
  • Strong proficiency in Python and modern backend development, including RESTful APIs and cloud-native deployment on AWS.
  • Hands-on experience with LLMs, prompt engineering, and RAG pipeline design.
  • Familiarity with vector stores, embedding models, and retrieval evaluation.
  • Comfortable working cross-functionally with non-engineering teams to scope and build internal tools.

Responsibilities

  • Design, build, and deploy AI-powered workflow tools for various business teams.
  • Gather requirements directly from business teams and conduct user acceptance testing (UAT) before tool deployment.
  • Define and maintain reference patterns for AI integration across the organization.

Skills

Cross-functional collaboration
Requirement gathering
Communication

Tools

Python
RESTful APIs
AWS
LLMs
Prompt engineering
RAG pipelines
Vector stores

Job description

SavvyMoney, Inc. is seeking a full-time AI Engineer to design and deploy AI-powered workflow tools for diverse business teams. You will gather requirements directly from users, perform UAT, and define reference architectures for AI integration while working remotely across the organization.

The role emphasizes hands-on AI/ML experience, Python and AWS backend development, and collaboration with non-engineering teams to deliver internal tooling that scales with business needs.

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