# Senior / Staff AI Engineer at Snorkel AI

- Company: Snorkel AI
- What the company does: Snorkel AI builds specialized training data, benchmarks, and evaluation environments that help frontier models and agents perform in high-stakes domains. Backed by Greylock, Lightspeed and GV.
- Company website: https://www.snorkel.ai
- Type: Startups (AI role)
- Level: Senior
- Location: New York City, NY (Hybrid); San Francisco, CA (Hybrid)
- Work setup: Hybrid
- Posted: 2026-09-08
- Apply by: 2026-10-23
- Apply: https://job-boards.greenhouse.io/snorkelai/jobs/6185944004
- Page: https://www.1752.vc/careers/jobs/snorkel-ai-senior-staff-ai-engineer/

## About the role

We're looking for AI Engineers who combine strong software and distributed systems fundamentals with experience operating AI systems in production. You'll build the infrastructure that lets teams create, experiment with, evaluate, and operate LLM and agentic workloads at significant scale - from synthetic data and evaluation pipelines to simulation environments, orchestration systems, and LLM infrastructure.

## What they're looking for

- Design and build infrastructure for running large-scale agentic workloads, including multi-step agents interacting with tools, external services, sandboxes, and simulated environments
- Build scalable synthetic data generation and automated labeling systems that allow teams to create, refine, and evaluate high-quality training and evaluation datasets
- Build orchestration and distributed compute systems for running thousands to millions of AI experiments and simulations reliably across heterogeneous compute environments
- Develop infrastructure for agent simulation environments, including environment provisioning, isolation, lifecycle management, and scalable execution
- Build and operate LLM infrastructure for routing, rate limiting, retries, caching, provider failover, cost attribution, and efficient execution across multiple model providers
- Instrument agent and model workloads so failures are observable and debuggable - capturing traces, model interactions, tool calls, environment state, evaluation results, latency, reliability, and cost

Tags: Engineering