A senior product engineer typically owns features end to end, from shaping the problem with users to shipping and maintaining the code. A strong candidate brings solid full stack or front end depth, good product judgment, and comfort working closely with researchers and internal teams. At a platform serving researchers and AI labs, care for data quality and reliable participant flows matters.
Howit fits the AI era
AI tools speed up coding, testing and prototyping, so the role leans more on deciding what to build and judging quality. The human parts stay central: understanding researcher needs, designing trustworthy flows, and keeping verified human data genuinely human.
How it builds AI experienceWorking here means building products that collect real human feedback for AI labs, which builds practical understanding of data quality and model evaluation. That experience can grow through shipping features that guard against fake responses and by learning how research and AI teams use the data.
Worth showing- End to end product delivery
- Full stack engineering
- Product judgment
- Data quality focus
- Working with researchers
This is our own read, written from the employer's posting and the company's Spotlight. The employer's posting is the source of truth for the role.
About ProlificA platform of
-verified human participants that researchers and AI labs use to collect real human feedback, at a time when AI-generated fake responses are becoming a growing problem in online research.
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