4 часа назад
Backend Software Engineer (AI)
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Backend Software Engineer (AI): Building scalable, secure, and resilient backend services and APIs for the DDN Infinia AI Data Platform with an accent on distributed systems, hybrid infrastructure, and control-plane orchestration. Focus on designing microservices with strong consistency, fault tolerance, observability, security, and reliable operation at petabyte scale.
Location: United Kingdom; on-site
Company
develops the Infinia AI Data Platform for large-scale hybrid on-premises and cloud environments.
What you will do
- Design and build scalable, high-performance distributed backend services for the platform control plane.
- Develop versioned REST and/or gRPC APIs for centralized management, automation, policy enforcement, and external integrations.
- Implement microservices supporting provisioning, scaling, upgrades, configuration, and full lifecycle management across on-premises and cloud environments.
- Build policy-driven orchestration, Infrastructure-as-Code integrations, RBAC, multi-tenancy, and enterprise self-service capabilities.
- Implement observability through logs, metrics, traces, events, alerting, diagnostics, and incident correlation.
- Design secure, fault-tolerant systems with disaster recovery and seamless upgrades or rollbacks.
Requirements
- 5+ years of experience in backend or distributed systems engineering.
- Strong experience designing and building microservices-based architectures and large-scale distributed systems.
- Proficiency in at least one modern backend language, such as Go, C++, Java, or Python.
- Experience designing and implementing REST and/or gRPC APIs.
- Deep understanding of distributed systems, including consistency, availability, and partition tolerance.
- Experience with cloud-native and containerized environments, Kubernetes, CI/CD pipelines, automated testing, and security principles.
Culture & Benefits
- Hands-on technical leadership with influence across engineering teams.
- Focus on code reviews, design reviews, engineering best practices, and API quality.
- Work on mission-critical AI and data workloads operating at petabyte scale.
- Emphasis on reliability, performance, security, compliance, and operational supportability.
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