Frontier Agents Engineer (Forward Deployed Engineering)
San Francisco, CA$180k - $225kFull-timePosted 5mo ago
About the role
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 technologies to transform models into reliable enterprise software.
Responsibilities
- Architect and deploy production AI systems that integrate with complex enterprise environments (cloud platforms, data warehouses, internal APIs, business applications, proprietary software)
- Design scalable agent architectures combining LLMs, retrieval, memory, tools, structured knowledge, and enterprise data into production workflows
- Build robust integrations enabling AI agents to 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 enabling safe evolution through continuous delivery and experimentation
- Operationalize modern AI quality systems to handle evolving models, prompts, and data
- Deploy evaluation harnesses (offline benchmarks, online experiments, goldens, regression suites, LLM-as-a-Judge)
- Implement tracing, observability, monitoring, guardrails, grounding, and safety mechanisms for production AI
- Collaborate with Applied AI engineers to productionize evaluation methodologies, retrieval strategies, reasoning architectures, and capabilities
- Rapidly evaluate new models, frameworks, evaluation methodologies, and tooling for safe production adoption
- Partner with enterprise customers to understand infrastructure, workflows, and translate problems into scalable production AI architectures
- Collaborate with customer engineers, ML engineers, platform teams, and product orgs to deploy AI into mission-critical workflows
- Identify reusable engineering patterns for multiple deployments
- Serve as primary technical advisor for strategic enterprise accounts
- Lead architecture discussions on distributed systems, AI infrastructure, enterprise integration, and deployment
- Document reusable patterns, deployment strategies, and operational best practices
- Improve platform with product, infrastructure, and Applied AI teams
- Architect and deploy enterprise AI systems and agent platforms across lifecycle
- Build integrations across cloud infrastructure and enterprise software
- Deploy AI agents into production environments
- Operationalize evaluation frameworks, guardrails, and observability
- Run production experiments and measure real-world business impact
- Continuously improve deployed AI systems using customer feedback and telemetry
- Develop expertise across Forward Deployed Engineering and Applied AI
- Design, build, evaluate, deploy, and improve frontier AI systems end to end
Qualifications
- 4+ years of software engineering experience with strong fundamentals in distributed systems, data structures, algorithms, and system design
- Strong Python programming skills with experience building production software
- 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 rapidly iterate toward production solutions
- Excellent communication skills and ability to work directly with enterprise engineering teams
Skills
Required:Distributed systems
Benefits
- comprehensive health, dental and vision coverage
- retirement benefits
- learning and development stipend
- generous PTO
- commuter stipend (eligible)
Last updated Oct 21, 2026. Interested? Apply on the company site.
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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