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Scale AI is seeking a Senior Frontier Agents Engineer to work directly with strategic enterprise customers on production AI systems. You'll architect, integrate, deploy, and operate AI agents that automate complex workflows and reason over enterprise knowledge at scale.
In this forward-deployed engineering role, you'll combine modern software engineering, distributed systems, cloud infrastructure, and frontier AI technologies to transform cutting-edge models into reliable enterprise software. Unlike traditional infrastructure roles, you'll work at the intersection of AI and enterprise engineering, designing production agent architectures that integrate seamlessly into complex customer environments including cloud platforms, data warehouses, internal APIs, and proprietary systems.
Key responsibilities include:
**Enterprise AI Systems**: Architect and deploy production AI systems that integrate into complex enterprise environments. Design scalable agent architectures combining LLMs, retrieval, memory, tools, and enterprise data. Build robust integrations allowing AI agents to safely interact with customer systems while meeting security, governance, and compliance requirements. Rapidly prototype new AI capabilities and evolve them into production-ready systems.
**AI Platform Engineering**: Build production infrastructure enabling frontier AI research to become reliable enterprise software. Develop agent runtimes, orchestration frameworks, context pipelines, execution services, and tool integrations. Engineer systems for reliability, observability, latency, scalability, retries, and graceful degradation. Design human-in-the-loop workflows combining AI automation with expert oversight. Build deployment patterns enabling safe evolution through continuous delivery.
**Production AI Quality**: Operationalize AI quality systems ensuring production agents remain reliable as models and data evolve. Deploy evaluation harnesses using offline benchmarks, online experiments, and LLM-as-a-Judge. Implement tracing, observability, monitoring, guardrails, and safety mechanisms. Partner with Applied AI engineers to productionize new evaluation methodologies and emerging capabilities. Rapidly evaluate newly released models and frameworks for safe adoption.
**Customer Innovation**: Partner directly with enterprise customers to understand their technical infrastructure and workflows. Translate ambiguous problems into scalable production AI architectures. Collaborate with customer teams to deploy AI into mission-critical workflows. Identify reusable engineering patterns across deployments.
**Technical Leadership**: Serve as primary technical advisor for strategic accounts. Lead architecture discussions spanning distributed systems, AI infrastructure, and enterprise integration. Document reusable patterns and best practices. Work with Scale's product, infrastructure, and AI teams to improve the platform.
