AI Recruiting Platform / System Distribution Engineer & Staff Platform Engineer / USA #347

Client / Project Name: USA / NDA
Work Format: fully remote / B2B
Location: Remote
Domain: AI Recruiting Platform
Team Size: 50 people in overall
Team: team in the US and Ukraine, work until 20-00 by CET

Description:
The largest AI recruiting platform built for growing professional recruiting firms worldwide. We help firm leaders scale by aligning their teams around a repeatable recruiting workflow, consolidating their full recruiting stack into one platform, and embedding AI intentionally & strategically.

About the role:
Are you a senior distributed system/backend engineer who dreams of architecting the backbone of a world-changing enterprise AI SaaS platform? We’re a small, elite team of builders obsessed with creating one of the greatest companies in the world—and we need you to help us scale the unscalable. You’ll work alongside a tight-knit crew of top-tier engineers, tackling problems that demand creativity, rigor, and a relentless drive to ship excellence.

Main Tech Stack: Ruby + Activerecord + PostgreSQL + Elasticsearch

Requirements
- 8+ years of experience with Ruby on Rails
- 4+ years of building distributed systems from the ground up — bonus if you’ve done it at scale for SaaS or AI workloads
- 4+ years of strong using such stack as Kafka, Kubernetes, gRPC, and you know when to ditch the hype for what actually works
- You think in terms of trade-offs, not dogma — CAP theorem debates are your happy place
- You’re a doer who thrives in small teams where your impact is massive and bureaucracy is zero
- At least strong B2 level

Responsibilities
- Design and build distributed systems that handle massive throughput, low-latency processing, and fault tolerance at scale
- Own the architecture of our core infrastructure — think data pipelines, real-time processing, and highly available services
- Collaborate with AI and product teams to ensure our systems don’t just keep up, but set the pace for innovation
- Solve hard problems: consistency, scalability, and performance in a world where downtime isn’t an option