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Staff Frontier Agents Engineer (Forward Deployed Engineering)

Scale AI· Enterprise Engineering
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San Francisco, CA$252k - $315k + equityfull-timePosted 5mo ago

About the role

Staff Frontier Agent Engineer focused on architecting, integrating, deploying, and operating production AI systems for strategic enterprise customers, combining software engineering, distributed systems, cloud infrastructure, and frontier AI to transform models into reliable enterprise software.

Responsibilities

  • Architect and deploy production AI systems that integrate into complex enterprise environments (cloud platforms, data warehouses, internal APIs, business apps, proprietary software).
  • Design scalable agent architectures combining LLMs, retrieval, memory, tools, structured knowledge, and enterprise data into reliable production workflows.
  • Build robust integrations enabling AI agents to safely interact with customer systems while meeting security, governance, and compliance requirements.
  • Rapidly prototype new AI capabilities and evolve prototypes into production-ready systems.
  • 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, fallback strategies, and graceful degradation.
  • Design human-in-the-loop workflows that combine AI automation with expert oversight.
  • Build deployment patterns allowing AI systems to evolve safely through CD and experimentation.
  • Operationalize modern AI quality systems to maintain reliability as models, prompts, and data evolve.
  • Deploy evaluation harnesses (offline benchmarks, online experiments, golden datasets, regression suites, 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 evaluation methodologies, retrieval strategies, reasoning architectures, and capabilities.
  • Evaluate newly released models, agent frameworks, evaluation methodologies, and tooling for safe adoption into production systems.
  • Partner directly with enterprise customers to understand 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 cross-deployment use.
  • Serve as primary technical advisor for strategic enterprise accounts.
  • Lead architecture discussions on distributed systems, AI infrastructure, enterprise integration, and deployment.
  • Document reusable architecture patterns, deployment strategies, integration frameworks, and operational best practices.
  • Collaborate with product, infrastructure, and Applied AI teams to improve the platform.

Qualifications

  • 8+ years of software engineering experience with strong fundamentals in distributed systems, data structures, algorithms, and system design.
  • Strong Python programming skills with production software experience.
  • Experience building or deploying AI-powered applications using modern LLM APIs, agent frameworks, MCP, retrieval systems, or vector databases.
  • Experience with cloud platforms (AWS, Azure, or GCP) and modern production infrastructure.
  • Strong problem-solving skills and ability to navigate ambiguous technical requirements and iterate toward production solutions.
  • Excellent communication skills and ability to work directly with enterprise engineering teams.

Skills

Required:Distributed systemsPythonLP/LLM APIs and agent frameworksCloud platformsCommunication with enterprise teams

Benefits

  • comprehensive health, dental and vision coverage
  • retirement benefits
  • learning and development stipend
  • generous PTO
  • commuter stipend (potential)
Last updated Oct 21, 2026. Interested? Apply on the company site.
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About Scale AI

Data-centric infrastructure to accelerate the development of AI

Scale accelerates the development of AI within organizations of any size to deliver critical business insights and operational efficiency. Its data-centric infrastructure platform leverages RLHF (Reinforced Learning with Human Feedback) to help organizations build the strongest AI models that supercharge their business, with customers across industries including Meta, Microsoft, U.S. Army, DoD’s Defense Innovation Unit, Open AI, General Motors, Toyota Research Institute, Brex, Instacart and Flexport.

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