Staff Research Engineer: Scalable Multi-Agent Systems

Fdetimes; New York (NY); Hybrid; USD 500,000 - 850,000; Full time

Job summary

Anthropic is seeking a generalist researcher-engineer to design and run large experiments, build scalable systems for very large agent teams, and derive actionable insights from complex data. You will bridge research and engineering, quickly turning vague questions into runnable experiments and robust results.

You will collaborate with cross-functional teams to ensure experiments are trustworthy, scalable, and aligned with safety and societal goals, contributing to a platform used across the

Qualifications

• Significant software engineering, ML or research engineering experience.
• Experience owning end-to-end projects or large-scale systems.
• Ability to design and run large experiments and extract insights.
• Strong quantitative thinking and attention to detail.
• Willingness to work across research and engineering teams.

Responsibilities

• Design, run and interpret large-scale experiments on agent teams, reasoning rigorously about what the data does and doesn't show
• Investigate how performance and efficiency change as team size, compute and task horizon grow, and find the bottlenecks that limit them
• Build and scale the systems that run very large agent teams reliably, and debug the failures that only appear at scale
• Design evaluations for long-horizon problems, and keep their results trustworthy
• Build the tooling and metrics that let researchers see what a large agent team is doing and why
• Partner with research teams across Anthropic so they can run their own experiments on the platform, and communicate findings clearly

Skills

Software engineering

ML engineering

Research engineering

End-to-end ownership

Education

Bachelor’s degree or equivalent

Tools

Distributed systems

LLMs/Agents

Benchmarks/evaluations

Job description

Anthropic is seeking a generalist researcher-engineer to design and run large experiments, build scalable systems for very large agent teams, and derive actionable insights from complex data. You will bridge research and engineering, quickly turning vague questions into runnable experiments and robust results.

You will collaborate with cross-functional teams to ensure experiments are trustworthy, scalable, and aligned with safety and societal goals, contributing to a platform used across the