프롬프트 엔지니어링과 컨텍스트 엔지니어링을 통해 AI 모델의 응답 스타일과 도구 활용 방식을 설계하고 최적화해요. 소프트웨어 엔지니어링 또는 연구 분야에서 2년에서 10년 이상의 경력이 필요해요. LLM 기반 시스템에 대한 기술적 이해와 프롬프트 및 메모리 시스템 설계 경험이 필수예요. 복잡한 개념을 다양한 이해관계자에게 설명할 수 있는 커뮤니케이션 능력을 갖춰야 해요.
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.
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.
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.
Recent experience working on modern LLM-driven products.
Experience working across teams or with external partners.
Experience designing evaluations or benchmarks for AI systems.
