Role: Enterprise AI - Platform Engineer
Location: New York City, Madison Square Park area
Reports to: Head of Engineering
Experience Level: 6+ years
Work Model: Hybrid, with regular in-office presence
As a Platform Engineer, You Will Build Core Platform Services Design, build, and operate the services that support the Enterprise AI platform, including platform infrastructure and the model gateway.
Enable Enterprise Deployment Create reliable deployment systems for client cloud accounts, dedicated instances, and sovereign environments.
Own Infrastructure and Delivery Systems Build and maintain CI/CD, infrastructure as code, and deployment tooling across environments using Kubernetes, Helm, Terraform or Pulumi, and GitOps practices.
Build for Reliability Design systems that support secure multi-tenant operation, reliable service ownership, and clear operational accountability.
Establish Observability Build observability across the platform using service-level objectives, structured logging, metrics, tracing, and alerting.
Build FinOps Visibility Develop telemetry that tracks model and compute costs by tenant.
The Anti-Sell Hands-on software engineering: This is not a cloud-operations or ticket-queue DevOps role. You must be able to write production software and contribute deeply to platform services.
Operational ownership: You will participate in on-call operations and incident response and help build the processes required to operate a production platform.
Deployment complexity: The platform must operate across client cloud accounts, dedicated instances, and sovereign environments.
Team accountability: The platform must be observable, operable, and maintainable by the team rather than dependent on one individual.
Our Enterprise AI Platform Engineers Typically Have Production platform engineering experience: Six or more years of platform or infrastructure engineering experience supporting production SaaS.
Customer-controlled deployment experience: Experience shipping a product that customers run in their own environment, including in a VPC, a self-hosted environment, or an air-gapped environment.
Strong software engineering depth: Deep expertise in at least one backend language, such as Go, Ruby, Python, or TypeScript, with the ability to read and work across the others.
Cloud and infrastructure expertise: 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.
Reliability and observability ownership: Experience carrying a pager, running incidents, and working with tools such as OpenTelemetry, Prometheus, or Datadog.
Data and platform systems experience: Familiarity with Postgres, object storage, queues, and vector stores.
Candidates whose experience is limited to cloud operations or ticket-queue DevOps without software engineering, or who have never operated multi-tenant systems, will not be a fit for this role.
Top-Tier Candidates Will Have - 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.
Values - We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
- We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
- We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.
Advantages of joining Turing - Work at the frontier of AI, helping the world's leading AI labs improve their most advanced models by building expert datasets, RL environments, and first-of-a-kind benchmarks.
- Contribute to leading-edge AI research and showcase your work at top conferences such as ICLR, ICML, and NeurIPS.
- Bring frontier AI innovation to the enterprise, applying lessons learned from leading AI labs to solve real-world business challenges.
- Collaborate with and learn from exceptional colleagues with deep AI experience from Google, Meta, Amazon, and other leading technology companies.
- Move at the pace of AI innovation, with the speed, ownership, and impact of a startup.
