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Текст:
Hirify AI/Оригинал
TL;DR
Software Engineer, Enterprise (AI): Building scalable backend infrastructure, APIs, distributed data systems, and deployment pipelines for production-grade enterprise GenAI products with an accent on reliability, performance, security, and multi-cloud deployment. Focus on designing AI model integration services, optimizing latency and throughput, managing cloud infrastructure, and scaling inference and orchestration systems across enterprise environments.
Location: London, UK
Company
Scale AI develops reliable AI systems, high-quality data, and full-stack technologies that help enterprises and governments build, deploy, and oversee AI applications.
What you will do
Design, build, and scale backend systems powering enterprise GenAI products across Scale's and customers' infrastructure.
Develop secure, efficient services and APIs integrating AI models with enterprise data sources.
Architect distributed systems for data processing, inference, and orchestration of large-scale GenAI workloads.
Optimize latency, throughput, cost, reliability, and scalability across hybrid and multi-cloud environments.
Manage AWS, Azure, or GCP infrastructure, including automation, observability, security, and deployment.
Collaborate with ML and product teams to bring GenAI models into production through model serving systems, APIs, and evaluation frameworks.
Requirements
4+ years of experience developing large-scale backend or infrastructure systems, with emphasis on distributed services, reliability, and scalability.
Proficiency in Python or TypeScript and experience designing high-performance APIs and backend architectures with FastAPI, Flask, Express, or NestJS.
Deep familiarity with cloud infrastructure, especially AWS and Azure, plus Kubernetes, Docker, and Terraform.
Experience with relational and NoSQL databases such as PostgreSQL and DynamoDB, including 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.
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 and ship reliable backend systems in fast-paced environments.
Collaborative mindset and willingness to work closely with ML, infrastructure, and product teams.
Culture & Benefits
Work on enterprise-scale GenAI systems and infrastructure for leading businesses, enterprises, and governments.
Inclusive and equal opportunity workplace committed to reasonable accommodations.
Applicants may be reconsidered for the same role after a 90-day waiting period.
Hiring process
Candidates are subject to a 90-day waiting period before reconsideration for the same role.
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