Own the multi-factor authentication orchestration layer — verification strategy, step-up logic, and user-level customization — balancing security strength against completion rate with measurable outcomes
Own the engineering standard for the FDE track, including solution architecture patterns, engineering practices, testing, evaluation, production readiness and operational support requirements.
Develop the competitiveness of engineering by implementing a continuous improvement approach to the Group's engineering processes & associated engineering practices, and digital development environments (Engineering Factories, Cloud platforms, etc.).
Develop and maintain Infrastructure-as-Code (IaC) and automation to enable consistent, repeatable, traceable and controlled provisioning, configuration and management of cloud infrastructure and application environments.
Candidates should possess Software Development skills to implement AI models, build applications or services, and work with relevant programming languages and frameworks.
Mentor junior AI engineers, set best practices for prompt engineering, RAG pipelines, and agent evaluation, and help build reusable AI infrastructure for the broader team.
Master's degree or above, with at least 3 years of hands-on experience in Reinforcement Learning (RL), Reinforcement Learning from Human Feedback (RLHF), or Reinforcement Learning with Verifiable Rewards (RLVR). Experience in Agent-related projects is preferred.