Build industry-leading distributed systems such as storage and computing to provide reliable infrastructure for massive data and large-scale business systems.
Develop and implement techniques and analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualisation software.
Apply data mining, data modelling, natural language processing, and machine learning to extract and analyse information from large structured and unstructured datasets.
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Establish prompt architecture standards — versioning, A/B testing, structured output schemas — and apply reasoning patterns (ReAct, CoT, ToT) appropriate to each agent use case.
Architect and build production agentic systems hands-on — agent harnesses, orchestration topologies (supervisor/worker, event-driven, parallel), A2A coordination patterns, and LLM gateway configuration; write code, resolve complex engineering problems, and set the quality standard through personal example.
Design and implement knowledge layer components: RAG pipelines (hybrid search, re-ranking, late chunking), MCP-connected knowledge sources, Text-to-SQL, Elasticsearch integration, and knowledge graph layers — selecting and tuning the right retrieval strategy per use case.
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Review design packages (electrical, mechanical, controls) and ensure production teams fully understand the build requirements.
Conduct build readiness reviews with production, quality, HSE, and supply chain teams to ensure all materials, drawings, jigs, and procedures are released before production start.
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Review design packages (electrical, mechanical, controls) and ensure production teams fully understand the build requirements.
Conduct build readiness reviews with production, quality, HSE, and supply chain teams to ensure all materials, drawings, jigs, and procedures are released before production start.
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Maintain proper documentation, revision control, and traceability of all design outputs in accordance with UTAC's design verification procedures.
Develop and maintain bump mask design rules and Design Failure Mode and Effects Analysis (DFMEA) based on bumping process capabilities and manufacturing requirements.
Collaborate with cross-functional teams, including Process Engineering, Assembly Engineering, Product Engineering, and suppliers, to establish and continuously improve bump mask design guidelines that minimize manufacturing risks and enhance product quality and yield.
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