Platform Engineer - Enterprise AI
New York, New York, United States
Posted 15h ago
Job Location
New York, New York, United States
Tech Stack
Remote Work Policy
On-site
Categories
AI Infrastructure Engineer
About the job
Enterprise AI is building the platform that enables reliable deployment of AI systems across enterprise environments. As a Platform Engineer, you will build and operate the core of Turing’s Enterprise AI platform, including platform services, the model gateway, multi-tenant infrastructure, CI/CD, infrastructure as code, and observability. The central challenge is creating repeatable deployments across environments Turing may not control, including client cloud accounts, dedicated instances, and sovereign installations. This role requires hands-on software engineering and operational ownership, with a focus on building production software and contributing deeply to platform services.
Responsibilities
- Design, build, and operate core platform services, including platform infrastructure and the model gateway.
- Create reliable deployment systems for client cloud accounts, dedicated instances, and sovereign environments.
- Build and maintain CI/CD, infrastructure as code, and deployment tooling using Kubernetes, Helm, Terraform or Pulumi, and GitOps practices.
- Design systems for secure multi-tenant operation, reliable service ownership, and clear operational accountability.
- Build observability across the platform using service-level objectives, structured logging, metrics, tracing, and alerting.
- Develop telemetry to track model and compute costs by tenant.
Requirements
- Six or more years of platform or infrastructure engineering experience supporting production SaaS.
- Experience shipping a product that customers run in their own environment, including in a VPC, self-hosted, or air-gapped environment.
- Deep expertise in at least one backend language (e.g., Go, Ruby, Python, TypeScript) and ability to work across others.
- Deep experience in at least one cloud and comfort working in a second, including private networking, KMS, IAM, Kubernetes, Helm, Terraform or Pulumi, and GitOps.
- Experience carrying a pager, running incidents, and working with observability tools like OpenTelemetry, Prometheus, or Datadog.
- Familiarity with Postgres, object storage, queues, and vector stores.
- Experience with model serving and model gateways (e.g., vLLM, LiteLLM, Triton).
- Experience implementing SOC 2 controls in CI.
- Experience deploying and operating AI systems in regulated or highly controlled environments.