Build and operate shared AI platforms: a multi-provider LLM gateway, an agent orchestration layer, an evaluation and monitoring layer, and a staff assistant.
Deep Learning Systems Architecture & Ownership : Design and own CNN, U-Net, and ViT systems for precision inspection, measurement, and defect classification. Own real-time anomaly detection from sensor and time-series product development data streams. Highest day-to-day output responsibility.
Oversee the various line of efforts with the multifaceted teams, including the research, product management, data science, to curate and chart AI strategies for the respective Centres of Excellence (COEs)
The Senior AI Harness Engineer joins the organisation’s AI development team to define and build the foundational engineering capabilities supporting AI models and agents at enterprise scale. This role is essential for enabling AI systems to operate securely, reliably, and efficiently across various domains within the organisation.
Design and build data architectures specifically optimised for AI agent consumption: structured data stores accessible via tool-calling APIs, vector knowledge bases for semantic retrieval, graph databases for relationship-based reasoning, and hybrid retrieval systems that combine keyword, semantic, and structured query approaches.
Large language Model Algorithm Development: Build domain-specific large language models (LLM/MLLM) for e-commerce, integrating domain knowledge to rapidly apply models to business scenarios.
Build global logistic and warehousing network, improve operations efficiency and reduce operational cost with data analysis, machine learning and operation research methods.