We are now hiring our first Product Manager to lead the development of GenAI-powered experiences. Youll work across multiple product lines to design and implement production-grade prompt architectures, embed AI agents into the user journey, and scale experimentation with cutting-edge LLM tools.
Product Team Member Prompt Engineer
This role blends hands-on AI development with product integration strategy. Youll collaborate with product managers and engineers to design, evaluate, and iterate on generative AI solutions including multi-step prompt chains, agent workflows, and LLM selection frameworks. Your work will shape how personalization evolves across the platform.
All About the Role:
Bring experience delivering products in SaaS startups or enterprise environments, with a deep understanding of market dynamics, customer needs, and the competitive landscape.
Design and refine context and prompt architectures (e.g., few-shot, chain-of-thought, tool use) that drive our LLM-powered features.
Select and evaluate models, frameworks, and orchestration tools (e.g., OpenAI, Claude, LangChain, RAG).
As part of the product team you will collaborate cross-functionally with developers, UX, BI, and Product Marketing to ensure product success across the board.
Collaborate with engineers to implement scalable agent-based workflows and integrate GenAI into the product.
Partner with Product Managers to define user-facing use cases and influence product direction with AI capabilities.
Develop internal tooling and evaluation frameworks to test prompt quality, model behavior, and UX alignment.
Act as a thought leader on prompt best practices, model safety, and responsible AI design across product squads.
Requirements: Must-Have Qualifications:
2+ years of hands-on product experience with LLM-based products, including prompt design or AI agents design.
Experience with GenAI product interfaces (e.g., chatbots, content editors, agents).
Proven ability to POC - design and iterate on prompts for models like GPT-4, Claude, or LLaMA, including few-shot and CoT techniques.
Familiarity with Python and prompt-engineering libraries or platforms (e.g., LangChain, LlamaIndex, vector DBs), RAG pipelines, model fine-tuning, and multi-agent orchestration.
Comfortable working closely with AI engineers and UX designers to bring AI features to production.
Excellent communication skills, with the ability to explain complex AI concepts to technical and non-technical stakeholders.
Nice-to-Have Experience:
Understanding of NLP, ML, or data science fundamentals especially around generation, embeddings, and evaluation.
Familiarity with experimentation platforms (e.g., A/B testing) and personalization frameworks.
This position is open to all candidates.