Responsibilities
- Design, build, and scale reliable backend systems for enterprise GenAI products across Scale and customer infrastructure.
- Develop secure, efficient core services and APIs integrating AI models and enterprise data sources.
- Architect distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads.
- Optimize backend latency, throughput, cost, reliability, and scalability across hybrid and multi-cloud environments.
- Manage and evolve AWS, Azure, or GCP infrastructure with automation, observability, and security practices.
- Collaborate with ML and product teams on model integration, model serving, and evaluation frameworks.
- Continuously improve the maintainability and production readiness of AI systems.
Requirements
- At least 4 years of experience developing large-scale backend or infrastructure systems with an emphasis on distributed services, reliability, and scalability.
- Proficiency in Python or TypeScript and experience designing high-performance APIs and backend architectures using frameworks such as FastAPI, Flask, Express, or NestJS.
- Deep familiarity with cloud infrastructure, preferably AWS and Azure, plus Kubernetes, Docker, and Terraform.
- Experience managing relational and NoSQL databases such as PostgreSQL and DynamoDB and building data pipelines for data-intensive applications.
- Hands-on experience with GenAI applications, model integration, or AI agent systems, including deploying, evaluating, and scaling AI workloads in production.
- Understanding of observability, CI/CD, and security practices for enterprise or multi-tenant services.
- Ability to balance rapid iteration with production-grade quality and collaborate effectively with ML, infrastructure, and product teams.
Tech Stack
Categories
About Scale AI
Scale’s mission is to develop reliable AI systems for the world’s most important decisions. We provide the high-quality data and full-stack technologies that power the world’s leading models, and help enterprises and governments build, deploy, and oversee AI applications that deliver real impact. The Scale Generative AI Platform allows customers to build, evaluate, and control advanced AI agents and applications that continuously improve. The Scale Data Engine provides the technology to collect, curate, and annotate high-quality datasets. Through our Scale Labs, we test models with rigorous benchmarks and novel research to ensure breakthroughs translate into systems people can trust. Scale powers the most advanced LLMs and generative models in the world through RLHF, data generation and model evaluation. We work with industry leaders like Meta, Cisco, DLA Piper, Mayo Clinic, Time Inc., the Government of Qatar, and U.S. government agencies including the Army and Air Force.