Backend Engineer, Enterprise AI
Turing is hiring a Backend Engineer, Enterprise AI in New York, United States. Level rates it ; you can apply on Turing.
Level's read on this job
- On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
- The posting mentions OpenAI, Anthropic and AI research among its tools and skills.
- Turing has 30 other open roles on Level.
- Posted in the last few days.
AI in this role
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: Backend Engineer, Enterprise AI
Location: New York City, Madison Square Park area
Reports to: Head of Engineering, Enterprise AI
Experience Level: 6+ years
Work Model: Hybrid, with regular in-office presence
Why Join Enterprise AI?
Enterprise AI is building the platform that enables enterprises to deploy and operate AI systems in production.
As a Backend Engineer, you will build the services and APIs behind the platform, including agent orchestration, model routing, enterprise integrations, identity and permissions, evaluation systems, and usage metering.
You will help harden the platform for multi-tenant, enterprise-grade operation while building features that allow customers to configure and operate AI systems with greater independence.
As a Backend Engineer, You Will
Build Core Platform Services
Design, build, and operate backend services and APIs that support agent orchestration, model routing, enterprise integrations, permissions, evaluation, and usage metering.
Build Reliable LLM Applications
Develop production systems using tool use, agent loops, retrieval, prompt versioning, and agent versioning.
Enable Enterprise Integrations
Build and maintain integrations with document stores, ticketing systems, data platforms, and other enterprise systems.
Build Secure Multi-Tenant Systems
Design data models, identity systems, permissions, and service boundaries that support secure operation across multiple tenants.
Own Features End to End
Take features from architecture through implementation, testing, deployment, observability, and ongoing operation.
Build for Reuse and Scale
Create connectors, services, and agent capabilities that can be reused across customers rather than rebuilt for each deployment.
The Anti-Sell
Production engineering, not prototyping: This is not a role for someone whose experience is limited to notebooks, demos, or early prototypes. You must have owned production software.
Backend depth: You will work on services, APIs, asynchronous job systems, identity, permissions, and integrations.
Enterprise complexity: The platform must support multi-tenant operation, enterprise identity systems, customer data permissions, and complex integrations.
End-to-end ownership: You will be expected to own meaningful backend product surfaces from design through production operation.
Our Backend Engineers Typically Have
Production backend experience: Six or more years as a backend or full-stack engineer working on production SaaS or enterprise platforms.
Strong services engineering: Deep experience with Python or TypeScript services, API design, asynchronous job systems, and production operations.
Enterprise identity and permissions: Hands-on experience with OAuth, OIDC, SAML, or SCIM, as well as multi-tenant data modeling and access control.
LLM application experience: Experience building production LLM features involving tool use, agent loops, retrieval, prompt versioning, or agent versioning.
Enterprise integration experience: Experience integrating with document stores, ticketing systems, data platforms, or other enterprise systems.
Production LLM ownership: A track record of shipping LLM features used by paying customers and owning production systems after launch.
Candidates whose experience is limited to notebooks or prototypes, or who have no multi-tenant or production ownership experience, will not be a fit for this role.
Top-Tier Candidates Will Have
- Experience working on agent framework internals.
- Experience implementing SOC 2 or similar controls.
- Experience building integrations for financial services or other regulated industries.
- Experience building on OpenAI or Anthropic APIs in a production environment.
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.
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.
How we rate this
Backend Engineer, Enterprise AI at Turing rates 83 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Also common in software engineer jobs at this level
Pay
- Typical software engineer job
- $167k
This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs
Questions you could be asked
- Tell me about a research question you investigated. What did you find?
- Walk me through how you've used OpenAI in your day-to-day work.
- What are the limits of Anthropic that you've run into, and how did you work around them?
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
Adapt your resume
- List these exact terms on your resume: AI Research, OpenAI, and Anthropic. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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