Senior Rails Engineer, AI Enablement

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NIR-YU

WebsiteLinkedInAll Job Openings

201 - 500 employees

💼 Consulting

📦 Logistics

📣 Marketing

Consulting • Logistics • Marketing

NIR-YU is a company dedicated to empowering small and medium enterprises (SMEs) by providing tailored nearshore staffing solutions. They focus on strategic recruitment of skilled nearshore professionals, offering cost-plus pricing for transparency and affordability. Their services include staff augmentation, staff leasing, talent acquisition, and employer of record (EoR), aimed at helping SMEs gain access to a skilled workforce from Latin America. By facilitating the hiring of remote talent and ensuring compliance with local regulations, NIR-YU allows businesses to enhance their teams with English-speaking professionals, optimize costs, and focus on growth strategies without the burden of setting up foreign entities.

📋 Description

• Build and ship features across a mature Ruby on Rails backend hosted on Heroku and two React applications hosted on Vercel • Work within a layered monolith supporting state machines, warehouse workflows, device records, and third-party integrations • Balance AI initiatives with platform reliability, maintainability, performance, and architecture standards • Build shared AI infrastructure across products and internal developer tooling • Create benchmarking frameworks and evaluation harnesses using historical company data before deployment • Implement confidence thresholds, input/output constraints, tool usage rules, audit logs, and safe failure or human escalation modes • Build AI-assisted workflows for device data normalization, serial-number resolution, and hardware classification • Build automated customer-support triage, semantic deduplication, and Linear ticket creation for product defects • Implement retrieval-augmented generation and search over physical asset, resale, and processing data • Construct permissioned agents for operational actions such as record updates and shipment checks • Introduce AI tools into engineering, QA, and DevOps workflows • Guide product leaders and engineers on practical AI use cases, limitations, and trade-offs

🎯 Requirements

• 5+ years of professional production experience in Ruby on Rails • Deep expertise with large monolithic architectures • Proven experience shipping LLM/ML features to production using RAG, structured outputs, tool-calling agents, and classification • Mandatory experience building AI evaluation and benchmarking frameworks • Track record designing confidence thresholds, human-in-the-loop review workflows, and error mitigation strategies • Hands-on React experience for testing, debugging, and frontend integration • Experience working with messy or incomplete datasets, including entity resolution and data normalization • Ability to cover at least 75% of EST business hours • Experience fine-tuning or adapting models using proprietary datasets • Background with serial numbers, hardware asset tracking, product catalogs, or physical logistics systems • Experience introducing AI adoption strategies inside established engineering organizations • Pragmatic, measurement-driven engineering approach • Ability to identify when deterministic or traditional software is safer and more effective than AI