AI Engineer (Personalized & Proactive Agent)

The role

This person will build Long-term Memory, Retrieval, and Personalization systems for Gleo AI. They will design context engineering strategies and develop proactive agent experiences for vehicle-based AI.

What you will do

• Build Long-term Memory, Retrieval, Personalization systems and Learning Loops.
• Design Context Engineering and Context Summarization strategies.
• Develop Proactive Agent Experience including recommendation and proactive intervention.
• Build Closed-loop Evaluation systems using Offline evaluation and Online A/B testing.
• Implement stable Production Capability using LLM, machine learning, or rule-based systems.

Required qualifications

• Master's degree or higher in Computer Science, Artificial Intelligence, or related fields.
• 4+ years of practical experience in AI/ML or software engineering.
• Experience applying core principles of LLM and Agentic AI to real services.
• Experience discovering problems and deriving improvement directions from real usage logs and data.
• Ability to structure and improve uncertain problems through hypothesis, experiment, and evaluation.
• Software development capability to design, implement, and operate production-level AI/ML systems.

Nice to have

• Research or development experience in Long-term Memory, Retrieval, User Modeling, Personalization, or Recommendation Systems.
• Development experience of Context-aware or Proactive Assistant using context signals like schedule, location, and movement patterns.
• Experience building data pipelines that connect user interaction data to User Profiles or Features.
• Experience experimenting and optimizing recommendation and proactive intervention policies using Ranking, Contextual Bandit, or Sequential Decision Making.
• Experience directly training and applying machine learning models like LLM Mid-training, Post-training, or recommendation/ranking to services.
• Experience combining On-device AI with Cloud AI or applying privacy and sensitive information processing principles to products.
• Experience evaluating and optimizing AI/LLM system quality, intervention timing, latency, cost, and reliability.

Before you apply

• Interview process includes document screening, 1st interview, 2nd interview, and compensation negotiation.
• Do not include prohibited information such as resident registration number, family relations, marital status, salary, photo, or physical conditions in the application.
• Employment may be canceled if false information is found in the application.
• Reference checks may be conducted after the interview process with the candidate's consent.
• A 3-month probation period may apply.

About the company

42dot develops Gleo AI, an LLM-based vehicle voice AI agent applied to the Hyundai The New Grandeur.