Clera Full-Stack Software Engineer at Clera building AI infrastructure for reinforcement learning environments. Responsible for designing and building user interfaces that make complex workflows clear and actionable.
Responsibilities
Join a growing product team building AI infrastructure for creating and evaluating reinforcement learning environments. You will combine full-stack engineering and product design to make technically complex workflows clear, useful, and actionable for users.
Design and build interfaces across the platform and marketplace, taking ideas from early concepts through launch.
Make agent runs, evaluation results, reward signals, and quality feedback understandable and actionable.
Partner with research and engineering teams to turn complex reinforcement learning and evaluation workflows into useful tools.
Talk with users, observe where they struggle, and improve the product based on feedback.
Create thoughtful interaction patterns and maintain high standards for usability, visual quality, and implementation.
Qualification
At least 3 years in design engineeringGood product judgmentFamiliarity with developer tools
Required
At least 3 years in design engineering, product design, or a similar role, with a track record of shipping product interfaces.
Primarily full-stack engineering experience, including front-end skills and demonstrated design-engineering work that turns designs into working interfaces.
A portfolio showing shipped work and strong visual design, plus experience improving products through user feedback.
Technical education or strong technical fundamentals, with the ability to understand complex concepts and explain them clearly.
Experience working closely with engineers and researchers; familiarity with developer tools, data-rich products, research software, AI agents, evaluations, reinforcement learning, or training data is useful.
Good product judgment, clear communication, and the ability to work independently in an early-stage environment. Experience creating reusable interface patterns is also valuable.
Preferred
Familiarity with developer tools, data-rich products, research software, AI agents, evaluations, reinforcement learning, or training data
