Member of Technical Staff (Model Behavior)

Perplexity
San Francisco +1 more
On-siteCareer-pivot friendly

Who this role is best for

Aimed at mid-level software engineers with experience in LLM-driven systems who can design and optimize prompts and context engineering strategies.

Best fit for

  • Mid-level software engineers with experience in LLM behavior shaping and context engineering
    — “Experience shaping LLM behavior through prompts, tool and skill design, or memory systems.”
  • Candidates with strong analytical and experimental problem-solving skills
    — “the ideal candidate for this role has a strong software engineering background, and an analytical, experiment-driven approach to solving challenging problems.”
  • Individuals who can translate technical concepts into clear communication for diverse stakeholders
    — “Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders.”

Things to consider

  • The role requires at least 2 years of software engineering or research experience
    — “2 to 10+ years of experience in software engineering or research.”

How to stand out

  • Highlight specific examples of context or prompt engineering you've implemented in past roles
    — “Design, test, and optimize the prompts, skills, tools, and memory that shape Perplexity responses across products, features, and use cases.”
  • Emphasize your ability to lead knowledge sharing and cross-team collaboration
    — “Help engineers across teams build intuition for prompt design and context engineering best practices.”
  • Demonstrate your grasp of LLM-driven and agentic systems in your technical background
    — “Strong background in software engineering fundamentals, and a technical understanding of LLM-driven and agentic systems.”
  • Showcase your track record in identifying AI system failure modes through research
    — “Identify inconsistencies and failure modes in model outputs through well-designed research projects.”
  • Demonstrate familiarity with modern prompting and alignment techniques from industry and academia
    — “Track the latest prompting, context engineering, and alignment techniques from industry and academia.”
Pace · SteadyCollaboration · HighAutonomy · MediumDecision Impact · TeamLevel · Mid

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • Design and optimize prompts and contexts for AI models
  • Conduct research on model outputs and inconsistencies
  • Develop self-improvement loops for AI systems
Typical background
software engineerAI researcherdata scientist

Skills & requirements

Required

Software EngineeringLlm-driven SystemsPrompt DesignContext EngineeringModel Behavior ShapingResearch And Analysis

Preferred

Modern Llm-driven Products ExperienceTeam CollaborationExternal Partner Work

Stack & domain

Software EngineeringLlm-driven SystemsPrompt DesignContext EngineeringResearchAnalysisEvaluationBenchmarkingCommunicationProblem-solvingTeamworkLeadershipAI ProductsModel BehaviorUser ExperiencePromptingAlignment Techniques

About the role

Original posting from Perplexity via Ashby

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.

Source: Perplexity careers (Ashby)

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