Software Engineer, Enterprise
Builds scalable backend systems, APIs, distributed services, and cloud infrastructure that bring enterprise GenAI workloads into production. Requires 4+ years of backend or infrastructure experience, proficiency in Python or TypeScript, and familiarity with cloud, containers, databases, and production AI systems.
About the job
Responsibilities
- Design, build, and scale backend systems powering enterprise GenAI products, focusing on reliability, performance, and deployment across Scale’s and customers’ infrastructure.
- Develop secure, efficient core services and APIs integrating 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 across hybrid and multi-cloud environments.
- Manage and evolve cloud infrastructure across AWS, Azure, or GCP, including automation, observability, and security.
- Collaborate with ML and product teams to bring GenAI models into production through APIs, model-serving systems, and evaluation frameworks.
- Continuously improve reliability and scalability using strong engineering practices.
Requirements
- 4+ years of experience developing large-scale backend or infrastructure systems, emphasizing distributed services, reliability, and scalability.
- Proficiency in Python or TypeScript.
- Experience designing high-performance APIs and backend architectures with frameworks such as FastAPI, Flask, Express, or NestJS.
- Familiarity with AWS or Azure cloud infrastructure.
- Experience with Kubernetes and Docker.
- Experience with Infrastructure as Code tools such as Terraform.
- Experience managing relational and NoSQL databases, including PostgreSQL and DynamoDB.
- Hands-on experience with GenAI applications, model integration, or AI agent systems.
- Understanding of deploying, evaluating, and scaling AI workloads in production.
- 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.
- Collaborative approach to working with ML, infrastructure, and product teams.
Skills
Python, TypeScript, FastAPI, Flask, Express, Nestjs, AWS, Azure, Kubernetes, Docker, Terraform, Postgres, DynamoDB, CI/CD, Observability
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