Platform Engineer - Enterprise AI

Turing • New York, NY

1d • Hybrid

About The Position

Turing is hiring a Platform Engineer for its Enterprise AI team in the Madison Square Park area of New York City. The role reports to the Head of Engineering and follows a hybrid work model with regular in-office presence. The engineer 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, deployment tooling, and observability. A central challenge is enabling repeatable deployments across environments Turing may not control, including client cloud accounts, dedicated instances, and sovereign installations.

This is a hands-on software engineering role, not a cloud-operations or ticket-queue DevOps position. The engineer will write production software, own operational outcomes, participate in on-call operations and incident response, and help establish processes that make the platform observable, operable, reliable, and maintainable by the team. The role also includes developing telemetry to track model and compute costs by tenant.

Turing works with frontier AI labs and Fortune 500 enterprises to develop AI datasets, research benchmarks, and end-to-end agentic AI systems for mission-critical workflows. The company describes its values as client first, startup speed, and AI forward. It is an equal opportunity employer and encourages applicants whose experience may not align perfectly with every qualification to apply.

Requirements

• Six or more years of platform or infrastructure engineering experience supporting production SaaS.
• Experience shipping products that customers run in their own environments, such as a VPC, self-hosted environment, or air-gapped environment.
• Deep expertise in at least one backend language, such as Go, Ruby, Python, or TypeScript, and ability to read and work across the others.
• Deep experience in at least one cloud and comfort working in a second.
• Experience with private networking, KMS, IAM, Kubernetes, Helm, Terraform or Pulumi, and GitOps.
• Experience carrying a pager, running incidents, and working with observability tools such as OpenTelemetry, Prometheus, or Datadog.
• Familiarity with Postgres, object storage, queues, and vector stores.
• Ability to write production software and contribute to platform services; experience limited to cloud operations or ticket-queue DevOps without software engineering is not a fit.
• Experience operating multi-tenant systems; candidates who have never operated multi-tenant systems are not a fit.

Nice To Haves

• Experience with model serving and model gateways, including vLLM, LiteLLM, or Triton.
• Experience implementing SOC 2 controls in CI.
• Experience deploying and operating AI systems in regulated or highly controlled environments.

Responsibilities

• Design, build, and operate services supporting the Enterprise AI platform, 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 across environments using Kubernetes, Helm, Terraform or Pulumi, and GitOps practices.
• Design systems that support secure multi-tenant operation, reliable service ownership, and clear operational accountability.
• Establish platform observability using service-level objectives, structured logging, metrics, tracing, and alerting.
• Develop telemetry that tracks model and compute costs by tenant.
• Write production software and contribute deeply to platform services.
• Participate in on-call operations and incident response and help build processes for operating a production platform.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed