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Текст:
Hirify AI/Оригинал
TL;DR
Backend Engineer (AI infrastructure): Building the first software platform that lets AI labs operate compute clusters from multiple providers as one fleet, with an accent on Go services, Kubernetes, Postgres, and customer-facing infrastructure. Focus on multi-tenant authorization, telemetry pipelines, idle GPU capacity, production on-call, and shaping the product directly with customers.
Location: Remote in North America; San Francisco, CA
Company
hirify.global is building a market and infrastructure platform that enables AI labs, research teams, and inference providers to buy, operate, monetize, and finance compute capacity.
What you will do
Build the first versions of a platform that lets customers manage clusters from multiple providers and their own sites as one compute fleet.
Develop backend services in Go against Kubernetes and Postgres, with a TypeScript console for customers.
Build visibility into cluster health, usage, spend, alerts, and idle GPU capacity.
Implement organizations, roles, authorization, and single sign-on across customer clusters.
Work directly with customers and research and infrastructure teams to identify problems, decide what to build, and ship solutions.
Carry a production pager and improve system reliability after incidents.
Requirements
Production experience building technically complex software with meaningful real-world impact.
Experience building multi-tenant systems with authorization, organizations, and tenant data separation.
Fluency with the Kubernetes API, not only Kubernetes deployment.
Experience building metrics, logs, or event pipelines that support operational dashboards and alerts.
Production Go experience, or sufficient systems background to ship production Go within the first month.
Ability to build the frontend for owned features, in addition to primarily backend and infrastructure work.
Production on-call experience for customer-dependent systems, including reducing pager noise over time.
Comfort working from customer problems and rough sketches rather than fully specified requirements, and working as an individual contributor.
Nice to have
ML or HPC infrastructure experience, including training clusters, Slurm, or job schedulers.
Experience building cloud consoles or developer platforms for engineers running real workloads.
Experience with enterprise identity, including SSO, SCIM, and identity-provider integrations.
Experience syncing or replicating large datasets across clusters or regions.
Culture & Benefits
Full-time role on a small senior team with direct access to leadership.
Work on a new product before its first version has shipped, with impact measured in days rather than quarters.
Competitive pay and meaningful equity.
Comprehensive healthcare, dental, and vision coverage for employees and dependents.
401(k) and unlimited paid time off.
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