Hybrid Rust Backend Engineer – AI Platform

at Factorial

• Job title: Rust Backend Engineer – AI Platform
• Job type: Full Time
• Experience level: Mid level, Senior
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Distributed Systems, Google Cloud Platform, Kubernetes, Microservices, NoSQL, Python, Rust, SQL
• Location requirements: Hybrid, Ghent, Belgium

About the role

• Rust Backend Engineer developing cloud-native backend services for AI model deployment and orchestration. Collaborate with multidisciplinary teams to build scalable AI deployment infrastructure.

Responsibilities

• Design, build, and maintain cloud-native backend services in Rust that support AI model deployment, inference, lifecycle management, and monitoring.
• Develop robust APIs and orchestration components to manage deployment workflows.
• Architect low-latency, high-throughput inference services optimized for real-time AI applications running in the cloud.
• Integrate backend systems with model registries, data processing pipelines, and monitoring tools to provide a seamless end-to-end AI lifecycle.
• Collaborate closely with AI researchers, DevOps, and hardware teams to co-design scalable deployment pipelines tailored for cloud environments.
• Implement observability and telemetry systems to monitor model performance, availability, and cost efficiency.
• Work with both SQL and NoSQL databases to manage model metadata, logs, and large-scale inference results.
• Deploy, scale, and operate workloads on Kubernetes, ensuring high reliability, elasticity, and performance across cloud environments.
• Continuously evaluate and adopt new technologies in Rust, backend systems, and AI infrastructure to keep the platform state-of-the-art.

Requirements

• BSc or MSc in Computer Science, Software Engineering, or a related field.
• 5+ years of proven experience in backend development, ideally building platforms, distributed systems, or AI/ML infrastructure.
• Strong proficiency in Rust, with experience building production-grade services.
• Experience developing backend services in Python is a strong plus.
• Solid understanding of API design, microservices architecture, distributed systems, and event-driven backends.
• Hands-on experience with databases (SQL and NoSQL) and scalable data storage solutions.
• Familiarity with cloud platforms (AWS, GCP, or Azure) and infrastructure-as-code practices.
• Experience with Kubernetes and container orchestration in production cloud environments is a strong plus.
• Experience building CI/CD pipelines for ML models or integrating with MLOps platforms (e.g., MLflow, Seldon, Kubeflow) is a plus.
• Knowledge of AI model deployment workflows and integrating inference systems with backend services is plus.
• Experience in a hardware/software co-design environment is a plus.
• Fluent in English; additional European languages (German, Dutch, Spanish, French, or Italian) are a plus.

Benefits

• A collaborative, innovation-driven environment with significant autonomy and ownership.
• Hybrid work model with flexible scheduling.
• Opportunity to build a cloud AI deployment platform that will power next generation AI systems.
• Chance to join one of Europe’s most ambitious companies at the intersection of AI and silicon engineering.