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Applied AI Engineer

Designs and ships production AI systems including agentic workflows, RAG pipelines, and LLM integrations for an AI-native ERP platform serving finance teams. Requires 3+ years backend experience and 2+ years production AI with Python proficiency.

180k – 240kSan Francisco, CANew York, NYML EngineeringHybrid3+ YOE

About the role

What You'll Do

  • Own AI features end-to-end: from designing agentic workflows and RAG pipelines to the infrastructure that runs them in production at scale.
  • Work on genuinely hard problems: financial data is structured, high-stakes, and unforgiving, making it one of the more interesting domains to apply LLMs to.
  • Build the evaluation frameworks and experimentation loops that turn good models into reliable, production-grade systems.
  • Partner directly with product and domain experts to push the frontier of what AI can do inside an ERP, not just what's been done before.

Who We're Looking For

  • 3+ years in a technical role with a strong foundation in backend systems, APIs, and cloud infrastructure
  • 2+ years shipping production AI systems with real users and real stakes, not research or prototypes
  • Hands-on experience with production LLM applications: RAG pipelines, agentic systems, or structured extraction
  • Proficiency in Python and comfort working across the full stack to deliver end-to-end features
  • Strong product instincts and a habit of thinking about user impact, not just technical correctness
  • Drawn to hard, ambiguous problems and energized by building in an environment where the playbook is still being written

Bonus Points

  • Background in fintech, ERP, or accounting software
  • Experience with fine-tuning or training models, not just inference
  • Familiarity with Python, Kotlin, Java, or TypeScript
  • Experience building AI systems that operate on structured financial or transactional data

Skills

PythonLLMsRAGAgentic WorkflowsBackend SystemsAPIsCloud InfrastructureStructured ExtractionFine-TuningEvaluation Frameworks

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