Software Engineer (Backend, Enterprise) (AI)

TL;DR

Software Engineer (Backend, Enterprise) (AI): Building and scaling backend infrastructure, APIs, and distributed data systems for production-grade enterprise GenAI products with an accent on reliability, performance, secure model integration, and multi-cloud deployment. Focus on designing high-throughput services, orchestrating large-scale AI workloads, optimizing latency and cost, and operating robust systems across enterprise environments.

Location: Budapest, Hungary

Company

Scale AI develops reliable AI systems, high-quality data, and full-stack technologies for leading models, enterprises, and government organizations.

What you will do

• Design, build, and scale backend systems that power enterprise GenAI products.
• Develop secure APIs and core services integrating AI models with enterprise data sources.
• Architect distributed systems for data processing, inference, and orchestration of large-scale AI workloads.
• Optimize services for latency, throughput, cost, reliability, and scalability across hybrid and multi-cloud environments.
• Manage cloud infrastructure, automation, observability, and security using AWS, Azure, or GCP.
• Collaborate with ML, infrastructure, and product teams to deploy models and AI applications into production.

Requirements

• 4+ years of experience developing large-scale backend or infrastructure systems.
• Proficiency in Python or TypeScript and experience designing high-performance APIs with frameworks such as FastAPI, Flask, Express, or NestJS.
• Strong knowledge of cloud infrastructure, Kubernetes, Docker, and Terraform; AWS and Azure experience is preferred.
• Experience with relational and NoSQL databases, including PostgreSQL or DynamoDB, and data-intensive pipelines.
• Hands-on experience with GenAI applications, model integration, or AI agent systems in production.
• Understanding of observability, CI/CD, security, distributed systems, and production-grade engineering practices.

Culture & Benefits

• Work on enterprise-scale AI systems used by leading organizations and government agencies.
• Collaborate across ML, infrastructure, and product disciplines in a fast-paced environment.
• Focus on inclusive and equal employment practices.
• Reasonable accommodations are available throughout the application and recruiting process.