Software Engineer (Backend), Enterprise
Remote • Budapest, Hungary
Posted 2mo ago
About the job
Scale AI is seeking a Backend Engineer to join their team and build the core infrastructure for large-scale GenAI systems. This role involves designing and implementing scalable APIs, distributed data systems, and robust deployment pipelines to ensure production-grade reliability and performance for enterprise AI products. You will be instrumental in shaping how AI systems are deployed and scaled in the real world, working at the forefront of the GenAI revolution and solving complex backend and infrastructure challenges. This is an opportunity to contribute to cutting-edge solutions that transform workflows and drive efficiency for major enterprises.
Responsibilities
- Design, build, and scale backend systems for enterprise GenAI products, focusing on reliability, performance, and deployment.
- Develop core services and APIs for secure and efficient integration of AI models and enterprise data sources.
- Architect scalable distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads.
- Optimize backend performance for latency, throughput, and cost in hybrid and multi-cloud environments.
- Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving automation, observability, and security.
- Collaborate with ML and product teams to deploy GenAI models into production via efficient APIs and serving systems.
- Continuously improve reliability and scalability of AI systems using strong engineering practices.
Requirements
- 4+ years of experience in developing large-scale backend or infrastructure systems, emphasizing distributed services, reliability, and scalability.
- Proficiency in Python or TypeScript, with experience designing high-performance APIs and backend architectures using frameworks like FastAPI, Flask, Express, or NestJS.
- Deep familiarity with cloud infrastructure (AWS and Azure preferred), including container orchestration (Kubernetes, Docker) and Infrastructure-as-Code tools (Terraform).
- Experience managing data systems (relational and NoSQL databases like PostgreSQL, DynamoDB) and building data-intensive application pipelines.
- Hands-on experience with GenAI applications, model integration, or AI agent systems, including deployment, evaluation, and scaling of AI workloads.
- Strong understanding of observability, CI/CD, and security best practices for enterprise or multi-tenant environments.
- Ability to balance rapid iteration with production-grade quality in fast-paced environments.
- Collaborative mindset, working effectively with ML, infra, and product teams.