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Member of Technical Staff (Model Behavior)

Perplexity

Palo Alto, CAJobNo compensation foundPosted 3w agoVerified open 4 days ago

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At a glance

Compensation
No compensation found
Location
Palo Alto, CA
Work Authorization
Not specified

Job overview

Perplexity is hiring a Member of Technical Staff (Model Behavior). Perplexity is hiring software engineers for the Model Behavior team to shape how its AI products behave, including response style, tool usage, skills, and memory. The team designs prompt and context engineering strategies to deliver high-quality user experiences across multiple domains and models. The ideal candidate has a strong software engineering background and an analytical, experiment-driven approach to solving challenging problems.

Key focus areas include Design, test, and optimize prompts, skills, tools, and memory that shape Perplexity responses, Build self-improvement loops to steer prompts, improve tool/skill use, and enhance memory recall, and Help experiment with and release new models.

Successful candidates bring 2 to 10+ Years Software Engineering Experience. Important skills include Context Engineering, Prompt Engineering, Tool Design, Skill Design, Memory Systems, and Software Engineering Fundamentals. Preferred (not required): Modern LLM-Driven Products, Working Across Teams, Working With External Partners, and Designing Evaluations For AI Systems.

Skills & qualifications

RequiredNice to have

Skills

Context EngineeringPrompt EngineeringTool DesignSkill DesignMemory SystemsSoftware Engineering FundamentalsTechnical Understanding of LLM-Driven SystemsTechnical Understanding of Agentic SystemsCommunicationExplaining Complex ConceptsModern LLM-Driven ProductsWorking Across TeamsWorking With External PartnersDesigning Evaluations for AI SystemsDesigning Benchmarks for AI Systems

Qualifications

2 to 10+ Years Software Engineering Experience

Full job description

About the Role We're hiring software engineers for the Model Behavior team to help shape how Perplexity’s AI products behave: the style of their responses, and the way they use tools, skills, and memory. The team designs prompt and context engineering strategies to deliver high-quality user experiences across multiple domains and models.

The ideal candidate for this role has a strong software engineering background, and an analytical, experiment-driven approach to solving challenging problems. You’ll work on context and prompt engineering to shape model behavior and style, and to guide how models use tools, skills, and memory across our products.

What you'll do

  • Context Engineering: Design, test, and optimize the prompts, skills, tools, and memory that shape Perplexity responses across products, features, and use cases. Build self-improvement loops to steer the prompt, improve tool/skill use, and improve the ability to draw on memory.

  • Model Releases: Help experiment with and release new models.

  • Research & Analysis: Identify inconsistencies and failure modes in model outputs through well-designed research projects, for both internal and production systems.

  • Knowledge Sharing: Help engineers across teams build intuition for prompt design and context engineering best practices.

  • Staying Current: Track the latest prompting, context engineering, and alignment techniques from industry and academia, and bring the best ideas back to the team.

What We're Looking For Required

  • 2 to 10+ years of experience in software engineering or research.

  • Strong background in software engineering fundamentals, and a technical understanding of LLM-driven and agentic systems.

  • Experience shaping LLM behavior through prompts, tool and skill design, or memory systems.

  • Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders.

Nice to have

  • Recent experience working on modern LLM-driven products.

  • Experience working across teams or with external partners.

  • Experience designing evaluations or benchmarks for AI systems.

You've read the whole posting — now see how you match it.