Member of Technical Staff (Model Behavior)
Perplexity is hiring a Member of Technical Staff (Model Behavior) for a remote role open to applicants in United States. It pays $200k-$330k a year and Level rates it ; you can apply on Perplexity.
Level's read on this job
- Level rates this role Builds AI ●●●●: the job is building AI systems.
- The posting lists this role as remote.
- Tools and skills the posting cites include LLMs, prompt engineering and context engineering.
- Level classifies it as a mid-level role.
- Level lists 130 other open roles at Perplexity.
AI in this role
Design prompt and context engineering strategies to shape Perplexity AI model behavior, tool usage, and memory systems.
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.
How we rate this
Member of Technical Staff (Model Behavior) at Perplexity rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Questions you could be asked
- How do you structure and test a prompt to get consistent output from a language model?
- Tell me about a project where context engineering was part of your work. What did you do?
- Tell me about a project where software engineering was part of your work. What did you do?
- Tell me about a project where evaluation was part of your work. What did you do?
- Walk me through how you've used LLMs in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: Prompt engineering, Context Engineering, Software Engineering, Evaluation, and LLMs. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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