Perplexity AI에서 Model Behavior Architect를 채용합니다. LLM 기반 제품의 품질을 높이기 위해 프롬프트 엔지니어링 전략을 설계하고, 자동화된 평가 파이프라인을 구축하는 핵심 역할을 수행합니다. Python 활용 능력과 AI 시스템 평가 및 벤치마크 설계 경험이 필수이며, 연구와 제품 개발의 교차점에서 모델의 행동 일관성을 책임질 3년 이상의 경력자를 찾습니다.
We're looking for a Model Behavior Architect to help build Perplexity's AI products and evaluations. You'll sit within our AI team and collaborate closely with research and product teams, designing prompt and context engineering strategies to deliver high quality user experiences across multiple domains and models.
This role is equal parts craft and science. You'll develop a deep understanding of our answer engine by pressure-testing model capabilities and working across our AI infrastructure (including system and tool prompts, skills, and evaluations) to create a stellar product experience for our users.
You'll serve as a go-to expert on prompting, model quality, and behavioral consistency across new product features and model releases.
Context Engineering: Design, test, and optimize context strategies and system prompts that shape answer engine behavior across products, features, and use cases.
Evaluation Systems: Build automated and semi-automated evaluation pipelines that measure model quality, catch regressions, and scale across product surfaces.
Model Launch Support: Partner with research and engineering to validate model behavior before and during rollouts, ensuring smooth transitions with no degradation.
Research & Analysis: Identify inconsistencies and failure modes in model outputs through well-designed research projects — for both internal and production-facing systems.
Cross-functional Collaboration: Work closely with design, product, and research teams to translate product goals into concrete model behavior requirements.
Knowledge Sharing: Help engineers across teams build intuition for prompt design, context engineering, and evaluation best practices.
Staying Current: Track the latest alignment, evaluation, and prompting techniques from industry and academia, and bring the best ideas back to the team.
Experience designing evaluations, benchmarks, or metrics for AI systems.
Strong written and verbal communication skills, particularly in explaining complex concepts to diverse stakeholders.
Ability to manage multiple concurrent projects in a fast-moving environment.
Strong experience with Perplexity or other frontier AI models in production settings.
Demonstrated experience with Python — you'll prototype, debug, automate, and build systems at scale.
3+ years of experience working with LLMs in a product or research setting.
Experience with A/B testing or experimentation frameworks.
Track record of improving AI system performance through systematic evaluation and iteration.
Get excited about edge cases in model behavior and love digging into how an answer could be better.
Enjoy turning qualitative "this feels off" intuitions into quantitative metrics and systematic fixes.
Want to work at the intersection of research and product, where your work ships to real users same-day.
Are comfortable with ambiguity and can define what "good" looks like for novel AI features.
Have a hacker spirit — you'd rather build a quick prototype to test a hypothesis than debate it in a doc.
Care deeply about making AI more reliable and useful for our users.
