Senior Rails Engineer & AI Platform Lead

Nir Yu; Mexico; Hybrid; PHP 8,521,000 - 12,781,000; Full time

Job summary

Nir Yu is seeking a senior Rails and Applied AI engineer to lead production-ready AI features on a mature Ruby on Rails monolith, with two React frontends hosted on Vercel. The role blends platform engineering, AI evaluation, and safe, scalable AI practices for real-world inventory and logistics systems.

The candidate will design evaluation harnesses, establish guardrails, and enable AI-driven workflows across engineering, QA, and DevOps, while balancing reliability and performance.

Qualifications

• 5+ years of professional production experience with Ruby on Rails and monolithic architectures.
• Proven experience shipping LLM/ML features to production using applied patterns (RAG, tool-calling, structured outputs).
• Experience building evaluation/benchmarking frameworks to measure AI accuracy.
• Design of guardrails including confidence thresholds, human-in-the-loop workflows, and error mitigation strategies.
• Frontend integration work with React to test and complete UI features.

Responsibilities

• Develop and ship features on a mature Rails backend (Heroku) and two React apps (Vercel).
• Balance AI initiatives with platform reliability and performance standards.
• Build shared AI infrastructure across products and internal tooling.
• Create AI evaluation harnesses to benchmark model performance on historical data.
• Implement guarded AI agents with strict authorization and audit logging.
• Enable AI adoption in daily engineering, QA, and DevOps workflows.

Skills

Ruby on Rails

React frontend

Applied AI in prod

AI evaluation harnesses

AI guardrails & safety

Tools

Rails monolith

Heroku

Vercel

Job description

Nir Yu is seeking a senior Rails and Applied AI engineer to lead production-ready AI features on a mature Ruby on Rails monolith, with two React frontends hosted on Vercel. The role blends platform engineering, AI evaluation, and safe, scalable AI practices for real-world inventory and logistics systems.

The candidate will design evaluation harnesses, establish guardrails, and enable AI-driven workflows across engineering, QA, and DevOps, while balancing reliability and performance.