4 дня назад
System Architect (Azure)
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
System Architect (Azure): Owning the architecture and development of a scalable, cloud-native, agentic system for integration with enterprise clouds, CRMs, and productivity suites with an accent on Kubernetes, Everything-as-Code, GitOps, and self-service products. Focus on standing up a greenfield Azure environment, building the integration layer, and driving an AI-assisted SDLC from proof of concept to production.
Location: Netanya, Israel
Company
Labs is a founder-led unit building an agentic solution for mid-market customers that integrates with major enterprise clouds, CRMs, and productivity suites.
What you will do
- Own the architecture of a scalable, cloud-native system from initial design through production.
- Stand up a greenfield Azure environment using Kubernetes, Everything-as-Code, GitOps, and CI/CD.
- Translate complex decisioning methodologies into self-service products with the Chief AI Officer.
- Write core code, set engineering standards, and guide engineers through technical decisions without direct people management.
- Build an agentic SDLC using AI coding agents across the development lifecycle.
- Design integrations with native agent and data surfaces across enterprise platforms.
Requirements
- 10+ years of software engineering experience with hands-on production experience architecting, shipping, and operating large-scale cloud-native systems.
- Current hands-on architecture and coding experience with strong Python skills; Go and Bash are advantageous.
- Production experience with Kubernetes, Terraform, Helm, GitOps, ArgoCD, CI-gated SDLCs, SLOs, observability, and blameless postmortems.
- Experience driving software development through AI coding agents.
- Readiness to work primarily with Azure; cross-cloud experience, including GCP, is advantageous.
- Ability to work effectively in an ambiguous, high-ownership, flat-team environment.
Nice to have
- Data engineering or data science experience, including pipelines, feature engineering, and data quality.
- Understanding of pricing or decision-support systems.
- Experience taking a product from proof of concept to general availability.
- MLOps, LLMOps, or platform engineering experience.
Culture & Benefits
- Small, flat, deliberately senior team with high trust and individual ownership.
- Fast POC-to-production delivery with minimal ceremony.
- Leadership through technical contribution rather than formal people management.
- Opportunity to design the foundation of an autonomous, agentic product.
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