Staff Frontier Agents Engineer (Applied AI)
San Francisco, CA$265k - $331kfull-timePosted 2mo ago
About the role
Staff Frontier Agents Engineer (Applied AI) at Scale AI focused on bridging cutting-edge AI research and production deployment to design, evaluate, and deploy intelligent systems that combine frontier models with structured knowledge, retrieval, traditional ML, and enterprise software for enterprise customers.
Responsibilities
- Design and deploy production AI agents that leverage the latest advances in large language models, reasoning, retrieval, memory, and tool use
- Architect intelligent systems that combine LLMs, traditional machine learning, structured knowledge, enterprise data, and deterministic software into reliable production workflows
- Engineer customer intelligence layers, retrieval pipelines, memory systems, and knowledge representations that allow agents to reason over large, heterogeneous enterprise data
- Develop multi-agent systems that coordinate reasoning, planning, tool execution, and human oversight
- Translate frontier AI research into production systems by rapidly evaluating new models, prompting techniques, reasoning paradigms, and agent architectures
- Own the full experimentation lifecycle, from hypothesis generation to production rollout
- Design rigorous evaluation frameworks using offline benchmarks, online A/B experiments, golden datasets, regression suites, LLM-as-a-Judge, and human evaluation
- Run controlled experiments and ablation studies to understand model/prompts/retrieval/reasoning/memory/architecture contributions
- Continuously evaluate newly released frontier models for quality, latency, reliability, or cost improvements
- Develop confidence estimation, reflection, and continuous learning systems that improve agents with real-world feedback
- Measure success through business outcomes, not benchmark scores
- Build production-quality AI systems emphasizing reliability, observability, latency, safety, and cost
- Design agent guardrails, fallback strategies, tracing, monitoring, and evaluation pipelines for safe deployment in high-stakes environments
- Collaborate with infrastructure engineers to deploy AI systems securely within enterprise cloud environments
- Build human-in-the-loop workflows that combine AI automation with expert oversight
- Partner directly with enterprise customers to understand their business, data, and operational challenges
- Translate ambiguous customer problems into production AI architectures
- Rapidly prototype ideas, validate with customers, and evolve solutions into scalable production systems
- Identify reusable patterns that become core capabilities across deployments
Qualifications
- 8+ years of software engineering, machine learning, or applied AI experience
- Strong Python programming skills
- Experience building production AI systems using LLMs
- Experience with OpenAI, Claude, MCP, agent frameworks, vector databases, or retrieval systems
- Strong understanding of machine learning fundamentals and modern language models
- Experience designing or evaluating AI systems using quantitative metrics
- Excellent communication skills and ability to work with enterprise customers
Skills
Required:PythonProduction AI systemsLLMs / Modern language models
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.
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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