3 months ago
Base Salary
$110k - $160k/yr
Responsibilities
- Own AI features end to end, from designing agentic workflows and RAG pipelines to building production infrastructure.
- Build AI systems that process structured, high-stakes financial data within ERP workflows.
- Create evaluation frameworks and experimentation loops for reliable production-grade AI systems.
- Partner with product and domain experts to expand AI capabilities inside an ERP.
- Deploy frequently, iterate quickly, and maintain high standards for production quality.
Requirements
- At least 3 years of experience in a technical role with a strong foundation in backend systems, APIs, and cloud infrastructure.
- At least 2 years of experience shipping production AI systems used by real users in high-stakes settings.
- 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.
- Experience with fintech, ERP, or accounting software is a bonus.
- Experience fine-tuning or training models, beyond inference, is a bonus.
- Familiarity with Python, Kotlin, Java, or TypeScript is a bonus.
- Experience building AI systems for structured financial or transactional data is a bonus.
Benefits
- New York City HQ location in EST.
- 27 PTO days including public holidays.
- Learning and development budget for courses, certifications, and language learning.
- High-autonomy early-stage role with direct product influence and a high-trust environment.
Tech Stack
Categories
About DualEntry
DualEntry builds an AI-native ERP and accounting suite for finance teams at growing and multi-entity companies, with modules for general ledger, revenue recognition, multi-currency, and real-time reporting. It sells the platform as cloud software that automates data entry and close processes, helping mid-market through public companies handle high-volume transactions. Founded in 2024 and headquartered in New York City, the company is privately held.