Staff Frontier Agents Engineer (Forward Deployed Engineering)

About the job

Responsibilities

• Architect and deploy production AI systems that integrate seamlessly into complex enterprise environments.
• Design scalable agent architectures combining LLMs, retrieval, memory, tools, and enterprise data.
• Build robust integrations for AI agents to safely interact with customer systems, meeting security and compliance requirements.
• Rapidly prototype new AI capabilities and evolve them into production-ready systems.
• Build production infrastructure for frontier AI research, including agent runtimes, orchestration frameworks, and context pipelines.
• Engineer systems for reliability, observability, latency, and scalability.
• Design human-in-the-loop workflows combining AI automation with expert oversight.
• Build deployment patterns for safe evolution of AI systems through continuous delivery.
• Operationalize AI quality systems to ensure production agents remain reliable.
• Deploy evaluation harnesses using benchmarks, experiments, and LLM-as-a-Judge to detect quality regressions.
• Implement tracing, observability, monitoring, guardrails, grounding, and safety mechanisms.
• Partner with Applied AI engineers to productionize new evaluation methodologies and capabilities.
• Rapidly evaluate new models, agent frameworks, and tooling for safe adoption into production.
• Partner directly with enterprise customers to understand their technical infrastructure and workflows.
• Translate ambiguous customer problems into scalable production AI architectures.
• Collaborate with customer teams to deploy AI into mission-critical workflows.
• Identify reusable engineering patterns for enterprise deployments.
• Serve as the primary technical advisor for strategic enterprise accounts.
• Lead architecture discussions spanning distributed systems, AI infrastructure, and production deployment.
• Document reusable architecture patterns, deployment strategies, and operational best practices.
• Work closely with internal 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 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.