Staff Frontier Agents Engineer (Applied AI)

TL;DR

Staff Frontier Agents Engineer (Applied AI): Designing and deploying production AI agents that combine frontier models with structured knowledge and enterprise data with an accent on reliability, observability, and scalability. Focus on bridging the gap between AI research and production by architecting multi-agent systems and rigorous evaluation frameworks.

Location: Based in the United States (referenced via US Department of Labor compliance)

Company

Scale AI is the data foundation for AI, helping organizations build and deploy reliable production AI applications for enterprises and government agencies.

What you will do

• Design and deploy production AI agents leveraging LLMs, reasoning, retrieval, memory, and tool use.
• Architect systems combining LLMs, traditional ML, structured knowledge, and deterministic software into reliable workflows.
• Develop multi-agent systems to coordinate reasoning, planning, tool execution, and human oversight.
• Own the full experimentation lifecycle and design rigorous evaluation frameworks using offline benchmarks and online A/B experiments.
• Build production-quality AI systems with a strong emphasis on reliability, observability, latency, and safety.
• Partner directly with enterprise customers to translate ambiguous business problems into production AI architectures.

Requirements

• 8+ years of software engineering, machine learning, or applied AI experience.
• Strong Python programming skills.
• Experience building production AI systems using LLMs.
• Proficiency with modern AI tooling including OpenAI, Claude, MCP, agent frameworks, or vector databases.
• Strong understanding of machine learning fundamentals and modern language models.
• Experience designing or evaluating AI systems using quantitative metrics.

Nice to have

• Experience with RAG, semantic search, knowledge graphs, or structured knowledge representations.
• Knowledge of fine-tuning, distillation, reinforcement learning, or model optimization.
• Experience building distributed production systems on cloud platforms (AWS, Azure, or GCP).
• Proficiency with Docker, Kubernetes, CI/CD, and production observability.
• Experience leading technical workshops and architecture reviews with enterprise customers.

Culture & Benefits

• Comprehensive health, dental, and vision coverage.
• Equity compensation and retirement benefits.
• Learning and development stipend.
• Generous PTO and commuter stipend.
• Inclusive and equal opportunity workplace environment.