AI Engagement Manager - Physical AI
Client Delivery / Physical AI · 3–5 years · Full-time · Korea · Open
About EBIT
EBIT started as an AI data company specializing in building, validating, and operating the high-quality training data that AI model development requires, and is now an AI solutions company expanding into Enterprise AI, Global GTM, and Physical AI.
EBIT provides an integrated data build service covering the entire process from data design to collection, processing, and quality control, along with custom data solutions optimized to each client's requirements. Since 2024 we have worked with big tech companies in Korea and abroad on high-complexity domain data projects across language, coding, STEM, and finance, establishing ourselves as an APAC partner. We are now growing fast, expanding into Enterprise AI solutions for corporate clients, Global GTM, and Physical AI areas such as robotics and autonomous driving.
About the Role
This is a dedicated account role for global Physical AI clients: you understand the data requirements for developing AI models that perceive and interact with the real world, such as robotics, embodied AI, and autonomous systems, and turn them into AI data projects.
Connecting the client's R&D teams with EBIT's project, data, and operations teams, you are responsible for successful delivery, client relationships, new data project discovery, and long-term partnership growth.
Responsibilities
Own global Physical AI accounts and partnerships
Serve as the main point of contact for clients in robotics, embodied AI, and autonomous systems, understand their R&D direction and data requirements, and build long-term partnerships.
Analyze client requirements and shape Physical AI data projects
Analyze the client's training and evaluation requirements and turn them into collection, processing, and validation projects for image, video, audio, sensor, spatial, trajectory, and other data types.
Coordinate between the client and internal project teams
Clearly convey the client's technical and operational requirements to internal program managers and the data, operations, and quality teams, and coordinate scope, schedule, data specifications, quality criteria, and key deliverables.
Manage project performance and data quality
Continuously track key metrics such as data quality, volume, coverage, acceptance rate, and delivery, and relay client feedback to internal teams to manage quality and client satisfaction.
Manage Physical AI data requirements and project risk
Understand requirements specific to Physical AI projects such as sensor configuration, collection environment, data specifications, and annotation criteria, and work with the client and internal teams on plans for risks such as spec changes, quality issues, collection conditions, and schedule.
Discover new projects and account expansion opportunities
Keep track of the client's robotics, embodied AI, and autonomous systems R&D roadmap and new model or system plans to identify new data needs and pilot projects, and expand the scope of collaboration with existing clients.
Requirements
- Education: Bachelor's degree or higher (any major; business, economics, industrial engineering, computer science, statistics, or information systems preferred)
- Experience: 3+ years in B2B client management, account management, consulting, or AI/data project management
- (Required) English proficiency sufficient to independently run meetings, project discussions, and communication with global clients
- Basic understanding of Physical AI fields such as robotics, embodied AI, and autonomous systems and the characteristics of their data
- Understanding of sensor data collected in real environments such as robots and autonomous vehicles, and of how AI models are trained and evaluated
Preferred
- Experience on Physical AI projects such as robotics, embodied AI, or autonomous driving/systems
- Experience directly managing global AI companies, robotics companies, AI labs, or overseas enterprise clients
- Experience analyzing and resolving client issues or project problems based on data and KPIs
