Senior / Staff Software Engineer (AI Platform)

Join our team as a Software Engineer (AI Platform) at Snorkel, where you'll build the infrastructure for large-scale AI workloads. You'll work on systems that require understanding behavior across models, prompts, tools, environments, and multi-step trajectories. This role offers the opportunity to collaborate with research, product, and engineering teams to turn experimental AI workflows into reliable, reusable platform capabilities. Enjoy comprehensive health benefits, unlimited PTO, and a supportive global team environment.

• Concevoir et construire l'infrastructure pour exécuter des charges de travail agentiques à grande échelle, y compris des agents à plusieurs étapes interagissant avec des outils, des services externes, des environnements simulés.
• Construire des systèmes de génération de données synthétiques évolutifs et des systèmes d'étiquetage automatisés qui permettent aux équipes de créer, de raffiner et d'évaluer des ensembles de données d'entraînement et d'évaluation de haute qualité.
• Collaborer avec les équipes de recherche, de produit et d'ingénierie pour transformer les flux de travail expérimentaux en capacités de plateforme fiables et réutilisables.

• Track record of leading complex engineering initiatives, influencing stakeholders, and delivering measurable impact
• Fluency with modern AI and developer tooling and a willingness to rapidly evaluate and adopt new models, frameworks, infrastructure, and techniques as the ecosystem evolves
• Strong background in distributed systems and cloud platforms (AWS preferred), including compute orchestration, storage, networking, isolation, and failure handling
• Strong understanding of production system fundamentals - observability, telemetry, reliability, performance, debugging, incident response, and cost management
• Experience operating non-deterministic AI or ML workloads in production or at significant scale — you are comfortable reasoning about behavior across models, tools, environments, and multi-step execution
• Ability to work in a fast-paced environment with strong technical communication skills
• Experience building infrastructure for experimentation, evaluation, model development, synthetic data, agentic workflows, training, inference, or production ML systems
• Experience with workflow or distributed execution frameworks such as Prefect, Airflow, Dagster, Ray, Kubernetes, or similar systems
• Strong proficiency in Python and experience building production-quality APIs, services, and developer tooling
• Ability to reason about AI system quality beyond traditional service metrics, including evaluation design, experiment reproducibility, behavioral regressions, and model or agent variability
• 5+ years building production software systems, with experience in AI/ML infrastructure, ML platforms, distributed systems, data platforms, or backend infrastructure
• Experience building or operating LLM or agent infrastructure, including model gateways, agent runtimes, tool execution, tracing, or multi-agent systems
• Experience with synthetic data generation, automated labeling, data refinement, or dataset quality systems
• Experience building evaluation or experimentation platforms for LLMs, agents, or other probabilistic systems
• Experience building reinforcement learning environments, agent simulations, benchmarks, or other environment-based evaluation systems
• Experience running large-scale distributed AI workloads across containers, Kubernetes, serverless compute, sandboxes, or heterogeneous compute environments
• Experience with LLM observability, tracing, prompt/version management, token and cost attribution, rate limiting, caching, or multi-provider routing
• Experience designing isolation and sandboxing infrastructure for executing model-generated code or tool calls safely
• Experience in hyper-growth startup environments or scaling engineering organizations
• Experience building shared AI platform libraries or SDKs consumed by multiple teams, including versioning, backwards compatibility, and migration support
• Prior experience as a Tech Lead, Team Lead, or hands-on Engineering Manager