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Senior / Staff AI Engineer

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Senior / Staff AI Engineer in USA

  • Snorkel AI
  • Full time
  • Email
  • San Francisco, CA

Responsibilities

  • Design and build infrastructure for large-scale agentic workloads interacting with tools, external services, sandboxes, and simulated environments.
  • Build scalable synthetic data generation, automated labeling, dataset refinement, and evaluation systems.
  • Develop evaluation infrastructure for reproducible experiments, benchmark execution, regression detection, and continuous evaluation.
  • Build orchestration and distributed compute systems for thousands to millions of AI experiments and simulations across heterogeneous environments.
  • Develop agent simulation environments with provisioning, isolation, lifecycle management, and scalable execution.
  • Build and operate LLM infrastructure for routing, rate limiting, retries, caching, provider failover, cost attribution, and efficient multi-provider execution.
  • Instrument AI workloads with traces covering model interactions, tool calls, environment state, evaluation results, latency, reliability, and cost.
  • Improve developer experience through APIs, SDKs, workflow abstractions, and tooling for moving workloads from local development to production.
  • Collaborate with research, product, and engineering teams to turn experimental AI workflows into reliable platform capabilities.

Requirements

  • 5+ years building production software systems, including experience with AI/ML infrastructure, ML platforms, distributed systems, data platforms, or backend infrastructure.
  • Experience operating non-deterministic AI or ML workloads in production or at significant scale.
  • Experience building infrastructure for experimentation, evaluation, model development, synthetic data, agentic workflows, training, inference, or production ML systems.
  • Strong proficiency in Python and experience building production-quality APIs, services, and developer tooling.
  • Strong background in distributed systems and cloud platforms, including compute orchestration, storage, networking, isolation, and failure handling; AWS is preferred.
  • Experience with workflow or distributed execution frameworks such as Prefect, Airflow, Dagster, Ray, Kubernetes, or similar systems.
  • Strong understanding of observability, telemetry, reliability, performance, debugging, incident response, and cost management.
  • Ability to evaluate AI system quality through evaluation design, experiment reproducibility, behavioral regression detection, and analysis of model or agent variability.
  • Track record of leading complex engineering initiatives, influencing stakeholders, and delivering measurable impact.
  • Strong technical communication skills and ability to work in a fast-paced environment.
  • Fluency with modern AI and developer tooling and willingness to evaluate and adopt evolving models, frameworks, infrastructure, and techniques.
  • Nice-to-have experience with LLM or agent infrastructure, evaluation platforms, synthetic data, reinforcement learning environments, large-scale distributed AI workloads, LLM observability, sandboxing, shared AI platform libraries or SDKs, hyper-growth startups, or prior Tech Lead, Team Lead, or hands-on Engineering Manager experience.

Benefits

  • Meaningful ownership over foundational AI infrastructure and architecture decisions.
  • Opportunities to shape priorities, influence strategic decisions, deepen technical expertise, and pursue leadership or learning opportunities.
  • The company offers a scaling environment with market-proven solutions, robust funding, and high-growth opportunities.

Snorkel AI

Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine platform technology with research-driven data development to create datasets, benchmarks, evals, and custom solutions for real-world AI systems. Founded...

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