Чётко очерченная senior-позиция SRE в быстрорастущей AI-компании даёт реальную ответственность за надёжность и работу с AI-инструментами, хотя культура быстрого темпа может быть требовательной.
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Высокий темпЧёткая зона ответственностиСфера искусственного интеллектаСовременная инфраструктураПоддержка развития
Оценка от Hirify AI
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Текст:
Hirify AI/Оригинал
TL;DR
Site Reliability Engineers (AI): Designing and operating resilient production systems for real-time AI voice, chat, and content platforms with an accent on disaster recovery, observability, incident response, and reliability automation. Focus on defining SLOs and SLAs, building AI-assisted investigation and remediation, and shaping architecture for resilience at scale.
Location: Remote and globally executable; optional offices in London, New York, San Francisco, and Warsaw.
Company
ElevenLabs is an AI research and product company building voice, chat, speech, music, image, and video platforms used by millions of users and thousands of businesses.
What you will do
Design and run disaster recovery programmes, define recovery targets, and test them regularly.
Define SLAs and SLOs with product teams and build tooling to track reliability by product and customer.
Own alerting, incident response, post-mortems, and on-call processes, driving corrective actions through completion.
Build AI-assisted investigation and auto-resolution capabilities, including agent-led diagnosis and automated remediation.
Work with product and engineering teams to shape resilient architecture and engineering practices at scale.
Requirements
Hands-on experience running production systems at scale as an SRE, infrastructure engineer, or in a similar role, with a track record of measurably improving reliability.
Strong backend development background and experience solving reliability problems with code and automation.
Experience owning incident response, on-call, and post-mortems, and driving fixes to completion.
Experience with observability and alerting, and with defining and tracking SLOs or SLAs.
Solid grounding in Kubernetes and cloud infrastructure; experience with GCP and AWS is preferred.
Culture & Benefits
High-velocity environment with rapid experimentation, autonomous teams, and minimal bureaucracy.
AI-first approach and emphasis on engineering excellence and measurable impact.
Annual discretionary stipend for professional development.
Annual discretionary stipend for meeting colleagues and an annual company offsite.
Monthly co-working stipend for employees not located near a main hub.
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