Job description preview
From Workist’s original posting
Your role with us As Senior Platform Engineer, you own the platform that Workist's AI agents run on: two clouds, the Kubernetes clusters for production, staging and ML workloads, and the path from merge request to production for every service we ship. You decide how this platform evolves, you keep it secure, observable and cost-efficient, and you extend it as the product grows. Most recently that meant an LLM gateway with region failover in front of our Azure OpenAI deployments, and performing GPU capacity planning for our own models. You set your own roadmap. Infrastructure at Workist is run as quarterly themes that you propose, make the case for and deliver, and roughly a third of your time goes to whatever the week brings: an incident, a pentest finding, a developer whose deployment is stuck and needs a second pair of eyes. You report to our CTO and are the voice of the platform in engineering decisions. How we build and run things • Everything runs on Kubernetes (Azure AKS), deployed with Helm and GitOps/Flux. All infrastructure is Terraform, applied through CI. • CI/CD for every service on GitLab • Managed services wherever they keep life simple: Postgres, OpenSearch, Redis,…
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