Software Engineer, Enterprise
Remote • London, UK
Posted 2mo ago
About the job
Scale AI is pioneering the next era of enterprise AI, providing cutting-edge solutions that transform workflows and automate complex processes for large enterprises. The Scale Generative AI Platform (SGP) offers foundational services and APIs for seamless AI integration at production scale. This role focuses on building the core infrastructure for large-scale GenAI systems, designing scalable APIs, distributed data systems, and robust deployment pipelines to ensure production-grade reliability and performance. It's an opportunity to solve hard backend and infrastructure challenges that enable AI to work at enterprise scale and shape how AI systems are deployed and scaled in the real world.
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 model serving systems.
- Continuously improve reliability and scalability using strong engineering practices for enterprise-ready AI systems.
Requirements
- 4+ years of experience developing large-scale backend or infrastructure systems, emphasizing distributed services, reliability, and scalability.
- Proficiency in Python or TypeScript, with experience in high-performance API and backend architecture design (e.g., FastAPI, Flask, Express, NestJS).
- Deep familiarity with cloud infrastructure (AWS and Azure preferred), including container orchestration (Kubernetes, Docker) and Infrastructure-as-Code (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.
- 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 for working with ML, infra, and product teams.