The opportunity
At Scale AI, we’re not just building AI tools—we’re pioneering the next era of enterprise AI. As businesses race to harness the power of Generative AI, Scale is at the forefront, delivering cutting-edge solutions that transform workflows, automate complex processes, and drive…
What you'll do
Design, build, and scale backend systems that power enterprise GenAI: products, focusing on reliability, performance, and deployment across both Scale’s and customers’ infrastructure.
Develop core services and APIs that integrate AI models and enterprise data: sources securely and efficiently, enabling production-scale AI adoption.
Architect scalable distributed systems for data processing, inference, and: orchestration of large-scale GenAI workloads.
Optimize backend performance for latency, throughput, and cost—ensuring AI: applications can operate at enterprise scale across hybrid and multi-cloud environments.
Manage and evolve cloud infrastructure (AWS, Azure, or GCP), driving: automation, observability, and security for large-scale AI deployments.
Collaborate with ML and product teams to bring cutting-edge GenAI models: into production through efficient APIs, model serving systems, and evaluation frameworks.
What they're looking for
- Continuously improve reliability and scalability , applying strong: engineering practices to make AI systems robust, maintainable, and enterprise-ready.
- + years of experience developing large-scale backend or infrastructure: systems, with a strong emphasis on distributed services, reliability, and scalability.
- Proficiency in Python or TypeScript , with experience designing: high-performance APIs and backend architectures using frameworks such as FastAPI, Flask, Express, or NestJS.
- Deep familiarity with cloud infrastructure (AWS and Azure preferred),: including container orchestration (Kubernetes, Docker) and Infrastructure-as-Code tools like Terraform.
