The Role:
This position supports a profitable and rapidly growing enterprise software and circular economy company specializing in IT asset lifecycle management and hardware repurposing to reduce electronic waste across major general corporations.
We are looking for a high-level hybrid profile: part Senior Rails Engineer, part Applied AI Engineer, and part internal AI Advisor. The organization is adopting AI capabilities in a deliberate and measured manner. The candidate will lead the development of production-ready features within a mature Ruby on Rails monolith while establishing the necessary evaluation harnesses, safety guardrails, and operational controls required for systems that impact real-world physical inventory and logistics.
Responsibilities:
- Rails Platform Engineering
- Build and ship features across a mature Ruby on Rails backend (hosted on Heroku) and two React applications (hosted on Vercel).
- Work within a mature, layered monolith supporting real-world physical operations (state machines, warehouse workflows, device records, and third-party integrations).
- Balance AI initiatives with core platform reliability, maintainability, performance, and architecture standards.
- AI Infrastructure, Evaluation & Guardrails
- Build shared AI infrastructure across products and internal developer tooling.
- Design AI Evaluation Harnesses: Create benchmarking frameworks and evaluation harnesses to measure model performance against historical company data before deployment.
- Establish Guardrails: Implement confidence thresholds, input/output constraints, tool usage rules, audit logs, and safe failure/human escalation modes when data is incomplete or ambiguous.
- Operational Domain AI Applications
- Device Data Normalization & Grading: Build AI-assisted workflows to normalize inconsistent device data, resolve serial numbers, and classify hardware using an A–D rating scale.
- AI Customer Support: Build automated triage, semantic deduplication, and automated Linea