Data and AI Architect , Professional Services - Taiwan

Amazon Amazon · Big Tech · TPE, Taiwan +1 · Solutions Architect

This role focuses on designing and implementing data and AI solutions, particularly generative AI architectures like RAG and fine-tuning, for industrial customers (manufacturing, semiconductor) on AWS. It involves end-to-end data architectures and leveraging AWS AI services.

What you'd actually do

  1. Lead the architecture design and delivery of data and AI solutions on AWS for strategic customers in Taiwan, with a focus on manufacturing and semiconductor verticals
  2. Design end-to-end data architectures including data lakes, data mesh, lakehouses, streaming analytics, and enterprise data warehouses using AWS services (e.g., Amazon S3, AWS Glue, Amazon Redshift, Amazon EMR, Amazon Kinesis, AWS Lake Formation)
  3. Architect and implement AI/ML solutions leveraging Amazon SageMaker, Amazon Bedrock, and other AWS AI services to address industry-specific use cases (predictive maintenance, yield optimization, defect detection, supply chain optimization)
  4. Collaborate with customers' technical and business stakeholders to define data strategies, roadmaps, and governance frameworks
  5. Lead technical workstreams within ProServe engagements, mentoring junior architects and consultants

Skills

Required

  • data engineering
  • data architecture
  • cloud architecture
  • designing and implementing data solutions on AWS
  • data platform technologies
  • data lakes
  • data warehouses
  • ETL/ELT pipelines
  • streaming architectures
  • data governance
  • Python
  • SQL
  • Spark
  • Scala
  • customer-facing skills
  • Mandarin Chinese
  • English

Nice to have

  • Domain expertise in manufacturing and/or semiconductor industries
  • Industry 4.0 / Smart Manufacturing initiatives
  • generative AI architectures
  • RAG patterns
  • foundation model fine-tuning
  • AI agents
  • data privacy and compliance requirements in the Taiwan market
  • large-scale data migration or modernization programs

What the JD emphasized

  • manufacturing and semiconductor industries
  • generative AI architectures including RAG patterns, foundation model fine-tuning, and AI agents

Other signals

  • design and implement modern data platforms, analytics solutions, and AI/ML workloads on AWS
  • architect and implement AI/ML solutions leveraging Amazon SageMaker, Amazon Bedrock, and other AWS AI services
  • generative AI architectures including RAG patterns, foundation model fine-tuning, and AI agents