Senior Frontier Agents Engineer (Forward Deployed Engineering)

About the job

Responsibilities

• Architect and deploy production AI systems integrating with complex enterprise environments, including cloud platforms, data warehouses, internal APIs, and business applications.
• Design scalable agent architectures combining LLMs, retrieval, memory, tools, structured knowledge, and enterprise data into reliable production workflows.
• Build robust integrations for AI agents to safely interact with customer systems while meeting enterprise security, governance, and compliance requirements.
• Rapidly prototype new AI capabilities and evolve successful prototypes into production-ready systems.
• Build production infrastructure for reliable enterprise software from frontier AI research.
• Develop agent runtimes, orchestration frameworks, context pipelines, execution services, and tool integrations.
• Engineer systems for reliability, observability, latency, scalability, retries, fallback strategies, and graceful degradation.
• Design human-in-the-loop workflows combining AI automation with expert oversight.
• Build deployment patterns for safe evolution of AI systems through continuous delivery and experimentation.
• Operationalize AI quality systems to ensure production agents remain reliable as models, prompts, and customer data evolve.
• Deploy evaluation harnesses using offline benchmarks, online experiments, golden datasets, and LLM-as-a-Judge to detect quality regressions.
• Implement tracing, observability, monitoring, guardrails, grounding, and safety mechanisms for production AI systems.
• Partner with Applied AI engineers to productionize new evaluation methodologies, retrieval strategies, reasoning architectures, and emerging AI capabilities.
• Rapidly evaluate newly released models, agent frameworks, evaluation methodologies, and developer tooling for safe adoption into production systems.
• Partner directly with enterprise customers to understand their technical infrastructure, software architecture, and operational workflows.
• Translate ambiguous customer problems into scalable production AI architectures.
• Collaborate with customer software engineers, ML engineers, platform teams, and product organizations to deploy AI into mission-critical workflows.
• Identify reusable engineering patterns for core capabilities across multiple enterprise deployments.
• Serve as the primary technical advisor for strategic enterprise accounts.
• Lead architecture discussions spanning distributed systems, AI infrastructure, enterprise integration, and production deployment.
• Document reusable architecture patterns, deployment strategies, integration frameworks, and operational best practices.
• Work closely with Scale's product, infrastructure, and Applied AI teams to continuously improve the platform.

Requirements

• Experience architecting enterprise AI systems and agent platforms.
• Experience building integrations across cloud infrastructure and enterprise software.
• Experience deploying AI agents into production environments.
• Experience operationalizing evaluation frameworks, guardrails, and observability.
• Experience running production experiments and measuring real-world business impact.
• Experience continuously improving deployed AI systems using customer feedback and operational telemetry.
• Experience working with the latest frontier AI models, evaluation methodologies, agent frameworks, and developer tooling.