Full Stack Engineer

Senior Full Stack EngineerWe’re looking for a senior infrastructure-focused engineer to design and operate the foundational systems that enable large-scale data creation, evaluation workflows, and AI experimentation. This role sits at the center of platform reliability, developer velocity, and data-intensive workloads.You’ll be responsible for building durable, extensible systems that support both research and product use cases—balancing speed, scale, and correctness in production environments.What You’ll DoDesign and implement core platform services that support data generation, task execution, evaluation workflows, and human‑in‑the‑loop processesBuild and maintain systems that reliably handle high‑volume data flows and compute‑intensive workloadsDevelop shared services, primitives, and APIs that empower engineers and researchers to ship faster with confidenceEstablish production‑grade observability, monitoring, and alerting to ensure system health and resilienceInfluence and shape the long‑term technical direction of data infrastructure, compute orchestration, and storage layersPartner closely with engineering and research teams to unblock new experimentation and platform capabilitiesDefine best practices around infrastructure design, deployment workflows, reliability standards, and operational excellenceRequired Qualifications5+ years of experience building, deploying, and owning backend or infrastructure systems in productionStrong proficiency with Python and/or JavaScript‑based backend frameworksHands‑on experience operating cloud‑hosted systems in AWS or GCP environmentsFamiliarity with event‑driven architectures and messaging systems such as Kafka, Pub/Sub, RabbitMQ, or similarExperience designing data‑intensive or asynchronous processing systemsSolid grasp of scalability, performance tuning, fault tolerance, and systems reliabilityDemonstrated ownership of systems running at meaningful production scaleExperience in fast‑moving, high‑bar engineering environments (e.g., top startups or large tech organizations)Preferred ExperienceBuilding or maintaining internal platforms used by multiple teamsOperating large data processing or analytics infrastructureExposure to machine learning platforms, model evaluation pipelines, or AI‑focused toolingExperience scaling early infrastructure in growth‑stage environmentsDesigning workflow engines or human‑in‑the‑loop systemsAdditional RequirementsExperience contributing to shared infrastructure, APIs, or platform abstractionsComfort owning architecture decisions across data pipelines, compute layers, and storage systemsStrong collaboration skills when working across engineering and research functionsUndergraduate degree from an accredited institution in the U.S., Canada, or the U.K.