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Agent Data Strategy — Product
This is not a traditional SaaS PM, nor a role that only writes PRDs and draws prototypes. We need someone who understands agent product forms, capability boundaries, and eval methods, and can go deep into real business scenarios to decompose complex tasks with domain experts. Your core output is real-scenario task definitions, expert-collaboration processes, task specs, and deliverable product plans — turning real business tasks into task environments and data products that agents can execute, evaluate, and iterate on.
What you’ll do
- 01Define cross-industry agent task scenarios — working with experts in law, finance, consulting, pharma, patents, compliance, design, and operations to decompose expert judgment and real workflows.
- 02Design agent evals and benchmarks — task design, metrics, rubrics, success criteria, and quality acceptance.
- 03Iterate task design, data standards, eval plans, and product processes based on model performance, expert feedback, customer needs, and delivery results.
- 04Use AI tools deeply for research, task decomposition, prototyping, data analysis, documentation, and workflow automation.
- 05Work with algorithm, engineering, and delivery teams to ship product plans into runnable task environments, eval systems, data pipelines, and customer deliverables.
What we look for
- 01Bachelor’s or above, any major — AI, CS, economics, management, law, finance, medicine, design, industrial engineering, information management, etc.
- 02AI-product or agent-product experience at big tech or a leading AI company — agent eval, benchmarks, model eval, complex-task assessment, AI product testing, or expert-labeling processes.
- 03Ongoing interest in agents, LLMs, post-training, eval, RL environments, and AI data pipelines.
- 04Strong task-decomposition ability — turning fuzzy business problems into clear processes, task units, judgment criteria, and acceptance rules.
- 05Experience working with domain experts, customers, frontline staff, or cross-functional teams — quickly grasping professional context and translating it into product language.
- 06Strong documentation — data plans, task specs, eval standards, expert guides, and customer deliverables.
- 07Comfortable with early-startup ways of working — ambiguity, self-direction, coordinating resources, and driving results.
Nice to have
- High-frequency AI-tool user, actively using AI to raise research, writing, analysis, prototyping, and delivery efficiency.
- Able to use AI tools or simple scripts for prototypes, data processing, workflow building, and efficiency tools.
- Your own views on agent product forms, capability boundaries, real-workflow automation, and AI-native ways of working.
Apply for this role
Send your résumé and a short note on why this role.