Senior / Staff AI Engineer
Snorkel AI · New York City, NY (Hybrid); San Francisco, CA (Hybrid)
About this role
**Senior / Staff AI Engineer** **About Snorkel** Snorkel believes meaningful AI starts with the data. We help enterprises transform expert knowledge into specialized AI at scale, working with some of the world's largest organizations to enable faster custom AI development. **About The Team** Snorkel's AI Platform organization builds infrastructure for AI development at scale—synthetic data generation, evaluation, agentic workflows, simulation environments, LLM infrastructure, and distributed compute. We're at the intersection of distributed systems and applied AI, shifting toward agent-first workflows. **The Role** We're hiring AI Engineers who combine strong software and distributed systems fundamentals with production AI experience. You'll build infrastructure for creating, experimenting with, evaluating, and operating LLM and agentic workloads at scale. **What You'll Do** • Design infrastructure for large-scale agentic workloads with multi-step agents, tools, and simulated environments • Build scalable synthetic data generation and automated labeling systems • Design evaluation infrastructure for measuring AI system behavior across models, prompts, and trajectories • Build orchestration and distributed compute systems for thousands to millions of AI experiments • Develop agent simulation environments with provisioning, isolation, and lifecycle management • Build LLM infrastructure for routing, rate limiting, caching, and multi-provider failover • Instrument workloads for observability—traces, model interactions, tool calls, and cost tracking • Design systems making non-deterministic workloads reproducible and measurable • Improve developer experience with APIs, SDKs, and workflow abstractions • Collaborate across research, product, and engineering teams **What You'll Bring** • 5+ years building production software systems (AI/ML infrastructure, distributed systems, or backend) • Experience operating non-deterministic AI/ML workloads in production at scale • Infrastructure experience with experimentation, evaluation, synthetic data, or agentic workflows • Strong Python proficiency and production-quality API/service building • Distributed systems and cloud platform expertise (AWS preferred) • Experience with workflow frameworks (Prefect, Airflow, Dagster, Ray, Kubernetes, etc.) • Production system fundamentals: observability, reliability, performance, debugging, cost management • Ability to reason about AI quality beyond traditional metrics • Track record leading complex engineering initiatives with measurable impact • Fast-paced environment adaptability and strong technical communication • Fluency with modern AI tooling and willingness to adopt new frameworks **Nice to Have** • LLM or agent infrastructure experience • Evaluation or experimentation platforms for probabilistic systems • Synthetic data generation or dataset quality systems • RL environments, agent simulations, or benchmarks • Large-scale distributed AI workloads across containers, Kubernetes, or serverless • LLM observability, tracing, or multi-provider routing • Isolation and sandboxing infrastructure • Shared AI platform libraries or SDKs • Hyper-growth startup or scaling organization experience • Tech Lead, Team Lead, or Engineering Manager background **Why This Role** You'll own infrastructure determining how quickly Snorkel experiments with and productionizes AI systems. Work on emerging infrastructure challenges: operating non-deterministic systems reliably,
Listing freshness
CronJobs last confirmed this listing 17h ago. If its source stops confirming the opening for seven days, this page is removed from active inventory.