Product Manager (Mobility Agentic Intelligence)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Define and deliver AI-driven experiences based on context generated throughout users’ Mobility Journeys. Analyze user actions, conversation, mobility context, and service reactions to shape product requirements, use cases, success metrics, and product roadmaps. Partner with Product, Engineering, and AI teams to coordinate scope and execution for connected mobility experiences spanning infotainment, navigation, mobile, and connected services, then continuously improve through launch validation.

Location: South Korea

Workplace: Hybrid

Employment Type: Full time

Job Function: Product Management

Seniority: Mid level

Key Responsibilities

•Shape product roadmaps and initiatives using environmental context and behavioral data from users’ Mobility Journeys.
•Analyze user journeys and AI agent/application usage to define product requirements and use cases.
•Define problems using user behavior data and service logs; establish product hypotheses and success metrics for validation.
•Coordinate product scope and execution plans with Product, Engineering, and AI teams across infotainment, navigation, mobile, connected services, and AI agents.
•Discover and develop user experiences such as personalization, recommendations, and memory-based AI services, then iterate post-launch based on user feedback and technical constraints.

Key Requirements

•5+ years leading product planning and execution as a Product Manager (or equivalent role).
•Translate user problems and business goals into product scope, requirements, priority, and drive roadmap/initiative execution.
•Use user behavior data, service metrics, and logs to establish and validate product hypotheses and success metrics.
•Connect the meaning and constraints of device signals, location/context data, interaction data, and service logs to define user context and use cases.
•Collaborate with engineering and AI teams to understand technical constraints and data availability, and make trade-off decisions between user value and product scope.

Experience:5+ yearsMobilityAutomotive softwareAI/MLConnected devicesPersonalization

Skills:CollaborationProblem definitionData-driven decision makingStrategic thinkingContinuous improvement

Tech Stack:AIAI AgentPersonalizationRecommendationsMemoryLocation/context dataService logsData modelingSchemaOntology

Company Brief

42dot

Website

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42dot

6 days ago

Product Manager (Mobility Agentic Intelligence)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 hour agoStatus: Live

Job Summary

Location: South Korea

Workplace: Hybrid

Employment Type: Full time

Job Function: Product Management

Seniority: Mid level

Key Responsibilities

•Shape product roadmaps and initiatives using environmental context and behavioral data from users’ Mobility Journeys.
•Analyze user journeys and AI agent/application usage to define product requirements and use cases.
•Define problems using user behavior data and service logs; establish product hypotheses and success metrics for validation.
•Coordinate product scope and execution plans with Product, Engineering, and AI teams across infotainment, navigation, mobile, connected services, and AI agents.
•Discover and develop user experiences such as personalization, recommendations, and memory-based AI services, then iterate post-launch based on user feedback and technical constraints.

Key Requirements

•5+ years leading product planning and execution as a Product Manager (or equivalent role).
•Translate user problems and business goals into product scope, requirements, priority, and drive roadmap/initiative execution.
•Use user behavior data, service metrics, and logs to establish and validate product hypotheses and success metrics.
•Connect the meaning and constraints of device signals, location/context data, interaction data, and service logs to define user context and use cases.
•Collaborate with engineering and AI teams to understand technical constraints and data availability, and make trade-off decisions between user value and product scope.

Experience:5+ yearsMobilityAutomotive softwareAI/MLConnected devicesPersonalization

Skills:CollaborationProblem definitionData-driven decision makingStrategic thinkingContinuous improvement

Tech Stack:AIAI AgentPersonalizationRecommendationsMemoryLocation/context dataService logsData modelingSchemaOntology

Company Brief

42dot

Website