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Member of Technical Staff (Software Engineer, Enterprise Agent Evals & Efficiency)
Perplexity AI · San Francisco, CA · Posted 18 days ago
"Build realistic enterprise evaluation environments and own the improvement loop that makes AI agents reliably complete multi-system workflows with less time and compute."
ABOUT THE ROLE
The Enterprise Agent Evals & Efficiency team makes Perplexity's agents better at completing real work across enterprise connectors, tools, and data. Our goal is to help agents choose the right tools, use the right context, and complete complex workflows reliably, with less time and compute. This team owns the improvement loop: define what successful work looks like, build evaluations that measure it, understand where agents fail, and ship changes that improve outcomes.
This is a hands-on engineering role with end-to-end ownership, from building realistic enterprise evaluation environments to shipping improvements across the agent harness, tools, and skills. You'll create complex scenarios spanning connected systems, data, and permissions, use them to identify where agents struggle, and improve the tools agents call, the skills they follow, the context they receive, and the models they use. Working with AI Research, Connectors, and Platform teams, you'll turn experimental results into measurable gains in task success, latency, and cost per successful task. The goal is not just to measure agents, but to make more enterprise work reliable and practical to automate.
KEY RESPONSIBILITIES
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This role is one of 695 Software Engineer openings in San Francisco, CA and centers on Python, Go, Rust, and Llm. There are 139 open roles at Perplexity AI right now.
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