8 hours ago
Responsibilities
- Design, build, and operate backend services and APIs for agent orchestration, model routing, enterprise integrations, permissions, evaluation, and usage metering.
- Develop production LLM applications using tool use, agent loops, retrieval, prompt versioning, and agent versioning.
- Build and maintain integrations with document stores, ticketing systems, data platforms, and other enterprise systems.
- Design secure multi-tenant data models, identity systems, permissions, and service boundaries.
- Own backend features from architecture and implementation through testing, deployment, observability, and ongoing operations.
- Create reusable connectors, services, and agent capabilities for scalable deployment across customers.
Requirements
- Six or more years of experience as a backend or full-stack engineer working on production SaaS or enterprise platforms.
- Deep experience with Python or TypeScript services, API design, asynchronous job systems, and production operations.
- Hands-on experience with OAuth, OIDC, SAML, or SCIM, along with multi-tenant data modeling and access control.
- Experience building production LLM features involving tool use, agent loops, retrieval, prompt versioning, or agent versioning.
- Experience integrating with document stores, ticketing systems, data platforms, or other enterprise systems.
- A track record of shipping LLM features used by paying customers and owning production systems after launch.
- Top-tier qualifications include experience with agent framework internals, SOC 2 or similar controls, regulated-industry integrations, and OpenAI or Anthropic APIs in production.
- Candidates must have production ownership and multi-tenant experience; notebook- or prototype-only experience is insufficient.
Benefits
- Hybrid work model with regular in-office presence in New York City.
- Opportunity to work at the frontier of AI and contribute to datasets, reinforcement learning environments, benchmarks, and enterprise AI deployments.
- Opportunity to contribute to leading-edge AI research and showcase work at ICLR, ICML, and NeurIPS.
- Collaboration with experienced colleagues from Google, Meta, Amazon, and other technology companies.
- Startup-paced environment with substantial ownership and impact.
Tech Stack
Categories
About Turing
Turing builds AI data pipelines and systems for enterprises and AI labs. It creates large-scale datasets and reinforcement-learning environments to train and evaluate models, and deploys agentic AI applications in domains like software engineering and enterprise workflows. The company also operates an AI-powered talent cloud to match and manage developers and AI trainers. Founded in 2018 and headquartered in San Francisco, it is privately held and serves Fortune 500 customers.