Turing’s mission is to accelerate superintelligence to drive real economic progress. Headquartered in San Francisco, Turing works with frontier AI labs to generate high-quality datasets, reinforcement learning environments, and frontier research benchmarks that improve model capabilities in software engineering, enterprise knowledge work, and advanced STEM reasoning. In software engineering, Turing is the largest and longest-running data provider in the category. Turing also works with Fortune 500 enterprises across financial services, life sciences, healthcare, retail, automotive, and CPG to build and deploy end-to-end agentic AI systems inside mission-critical workflows. By operating on both sides, Turing closes the loop between frontier research and enterprise deployment, turning real-world deployment signals into better data, evaluations, and more capable models. Learn more at www.turing.com.
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
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.
As a Platform Engineer, You WillBuild Core Platform ServicesDesign, build, and operate the services that support the Enterprise AI platform, including platform infrastructure and the model gateway.
Enable Enterprise DeploymentCreate reliable deployment systems for client cloud accounts, dedicated instances, and sovereign environments.
Own Infrastructure and Delivery SystemsBuild and maintain CI/CD, infrastructure as code, and deployment tooling across environments using Kubernetes, Helm, Terraform or Pulumi, and GitOps practices.
Build for ReliabilityDesign systems that support secure multi-tenant operation, reliable service ownership, and clear operational accountability.
Establish ObservabilityBuild observability across the platform using service-level objectives, structured logging, metrics, tracing, and alerting.
Build FinOps VisibilityDevelop telemetry that tracks model and compute costs by tenant.
The Anti-SellHands-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 HaveProduction 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.
- 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.
- 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.
Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you’re excited about this role but your past experience doesn’t align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review Turing's GDPR notice here.
Skills Required
- Six or more years of platform or infrastructure engineering experience supporting production SaaS
- Experience deploying products into customer-controlled environments, including VPC, self-hosted, or air-gapped environments
- Deep expertise in at least one backend language such as Go, Ruby, Python, or TypeScript
- Experience with cloud infrastructure, private networking, KMS, IAM, Kubernetes, Helm, Terraform or Pulumi, and GitOps
- Experience with reliability engineering, on-call operations, incident response, and observability tools such as OpenTelemetry, Prometheus, or Datadog
- Familiarity with Postgres, object storage, queues, and vector stores
- 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
Turing Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Turing and has not been reviewed or approved by Turing.
-
Fair & Transparent Compensation — Feedback suggests USD-denominated pay and access to higher-paying clients can outpace local benchmarks for many non‑U.S. developers. Payout timing and processing are described as predictable once engagements begin, which supports confidence in earnings.
-
Wellbeing & Lifestyle Benefits — Feedback suggests remote‑first work with flexible hours is a consistent positive that enhances day‑to‑day balance. The ability to work from anywhere and maintain autonomy is frequently highlighted as part of the overall rewards experience.
-
Healthcare Strength — Feedback suggests some U.S. corporate roles include comprehensive health benefits, with individual accounts referencing employer‑covered medical insurance. These signals indicate stronger healthcare support for certain employee populations.
Turing Insights
What We Do
We now live in a remote-first world and every company is in a race to find the best remote engineers. There are so many amazing engineers all over the world. Turing’s mission is to help unleash the world’s untapped human potential. More than 300 companies, including those backed by Google Ventures, Bloomberg, Andreessen, Founders Fund, and Kleiner are already using Turing to spin up their engineering dream teams. Turing’s hiring platform combines the planetary reach and AI to deliver your ideal engineers in order to help you spin up your engineering dream team. Our deep matching intelligence finds the best Turing developers across 100+ skills like React, Node, Python, Golang, Angular, Swift, Java, and many more. As part of our rigorous vetting process, we also review software engineers’ technical abilities, English skills, and remote working capabilities. Turing ensures time zone overlap, transparency, and reliable communication in order to make remote development easy for you after the match. The Turing team has deep expertise in AI and building engineering dream teams in the U.S. at top companies. Turing company is backed by well-known investors like Facebook’s initial CTO (Adam D’Angelo), executives from Google, Facebook, Amazon, Twitter, Founders Fund (investors in Facebook, Tesla, Asana, etc). Turing.com is led by serial A.I. entrepreneurs Jonathan Siddharth and Vijay Krishnan, their last A.I. firm leveraged remote talent and had a successful acquisition.
