Senior Frontier Agents Engineer

About the role

This position involves bridging the gap between advanced AI research and real-world production environments. You will design and deploy intelligent agent systems for enterprise clients, working across diverse industries to solve complex business problems.

Key facts

What you'll do

• Architect and deploy production-grade AI agents using LLMs, memory systems, and tool execution.
• Build retrieval pipelines and knowledge representations that allow agents to reason over enterprise data.
• Develop multi-agent systems capable of planning, coordination, and human-in-the-loop oversight.
• Create evaluation frameworks using offline benchmarks, golden datasets, and LLM-as-a-Judge metrics.
• Perform ablation studies to optimize model performance, latency, and cost.
• Implement safety guardrails, monitoring, and observability for high-stakes deployments.
• Partner with enterprise customers to translate business requirements into technical AI architectures.

Requirements

• 5+ years of experience in software engineering, machine learning, or applied AI.
• Proficiency in Python.
• Proven track record of building production AI systems using LLMs.
• Experience with modern AI tooling such as OpenAI, Claude, MCP, agent frameworks, or vector databases.
• Strong grasp of machine learning fundamentals and modern language models.
• Ability to design quantitative evaluation metrics for AI systems.
• Strong communication skills for direct customer interaction.

Nice to have

• Experience building autonomous agents or RAG systems.
• Knowledge of fine-tuning, distillation, reinforcement learning, or small language models.
• Familiarity with multimodal AI systems.
• Experience with distributed systems, cloud platforms (AWS, Azure, GCP), Docker, and Kubernetes.
• Background in leading technical workshops or architecture reviews.

Skills & tools

• Python
• LLMs (OpenAI, Claude)
• Agent Frameworks
• Vector Databases
• Retrieval Systems
• RAG
• Knowledge Graphs
• Cloud Infrastructure (AWS, Azure, GCP)
• Docker & Kubernetes
• CI/CD & Observability

Practical notes

• Compensation includes base salary, equity, and benefits such as health, dental, vision, retirement plans, and a learning stipend.
• Scale AI enforces a 90-day waiting period for candidates reapplying for the same role.
• Reasonable accommodations are available for applicants with disabilities by contacting accommodations@scale.com.