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Scale AI is seeking a Frontier Agents Engineer to bridge cutting-edge AI research and production deployment. You'll work directly with enterprise customers across finance, healthcare, manufacturing, media, and telecommunications to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional machine learning, and enterprise software.
In this role, you'll own the full lifecycle of modern AI systems: designing reasoning and agent architectures, building retrieval and memory systems, developing predictive models that work alongside LLMs, running rigorous experiments and ablation studies, shipping production systems into enterprise environments, and measuring business impact through online experimentation.
Key responsibilities include:
**Frontier AI Systems**: Design and deploy production AI agents leveraging the latest advances in large language models, reasoning, retrieval, memory, and tool use. Architect intelligent systems combining LLMs, traditional ML, structured knowledge, and enterprise data into reliable workflows. Engineer customer intelligence layers and multi-agent systems that coordinate reasoning, planning, and human oversight.
**Experimentation & Evaluation**: Own the full experimentation lifecycle from hypothesis to production rollout. Design rigorous evaluation frameworks using offline benchmarks, A/B experiments, golden datasets, LLM-as-a-Judge, and human evaluation. Continuously evaluate newly released frontier models and develop confidence estimation systems that improve agents over time using real-world feedback.
**Production AI Engineering**: Build production-quality systems with emphasis on reliability, observability, latency, safety, and cost. Design agent guardrails, fallback strategies, tracing, and monitoring pipelines. Collaborate with infrastructure engineers to deploy securely within enterprise cloud environments and build human-in-the-loop workflows.
**Customer Innovation**: Partner directly with enterprise customers to understand their business challenges. Translate ambiguous problems into production AI architectures. Rapidly prototype ideas, validate with customers, and evolve solutions into scalable systems. Identify reusable patterns that become core capabilities.
Unlike traditional ML roles focused on a single model, you'll work across a diverse portfolio of AI challenges spanning multiple industries and use cases—from multi-agent research systems to customer intelligence platforms, healthcare copilots, and autonomous workflows for Fortune 100 companies.
