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.
About the job
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
Python, LLMs, RAG, Agentic Workflows, Backend Systems, APIs, Cloud Infrastructure, Structured Extraction, Fine-Tuning, Evaluation Frameworks
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