Backend Platform Engineer — AI-Native SaaS

Full-Time · Remote · Europe / Ukraine Salienci.ai is building an AI-native operating system focused on Recommendation Authority™ — helping businesses understand and improve how AI systems recommend, cite, and select them. We are NOT looking for a generic backend developer or AI automation freelancer. We are looking for a systems-oriented backend/platform engineer who can stabilize and govern an evolving AI-assisted codebase. A large portion of the platform was built using AI-assisted engineering workflows. The system works — until hidden inconsistencies appear: • hallucinated DB fields, • non-idempotent migrations, • duplicated logic, • configuration drift, • silently broken assumptions, • and AI-generated code that looks correct but was never fully validated. Your role is to: • identify operational and architectural problems, • prove what is wrong, • stabilize the platform, • improve testing and validation discipline, • and help establish reliable AI-assisted engineering workflows that scale safely. What We Need • Strong backend/platform engineering experience • Python + FastAPI • PostgreSQL • Docker • CI/CD workflows • Strong debugging and production problem-solving skills • Systems thinking and operational discipline • Experience working with evolving specifications • Healthy skepticism toward AI-generated code • Ability to reduce complexity, not increase it Strongly Preferred • Kubernetes • AWS • RabbitMQ / Redis • Event-driven systems • Observability / monitoring • Multi-module SaaS platforms • AI/LLM infrastructure • LangGraph / orchestration workflows This Role Is NOT For You If • You trust AI-generated code without verification • Your workflow is “ask Claude/GPT to fix it” • You optimize for speed over reliability • You avoid debugging and operational ownership Application Requirements Please provide: • Resume/CV • GitHub profile • Examples of systems you built or stabilized Also answer this: Tell us about a time you inherited AI-generated or unstable production code. What was wrong, how did you identify it, and what did you do to prevent the problem from happening again? We are hiring for: • systems thinking, • operational rigor, • architecture discipline, • debugging depth, • and long-term platform stability. Strong engineering judgment matters more than flashy AI demos.