Data and AI Architect , Professional Services - Taiwan

Amazon is hiring a Data and AI Architect , Professional Services - Taiwan in Taipei, Taiwan. Level rates it ; you can apply on Amazon.

Level's read on this job

Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
Tools and skills the posting cites include Bedrock, SageMaker and AWS.
Level classifies it as a senior role.
Level lists 20,000+ other open roles at Amazon.

AI in this role

Data and AI Cloud Architect designing modern data platforms and AI/ML workloads on AWS for enterprise manufacturing and semiconductor clients.

BedrockSageMakerAWSAmazon SageMakerAmazon BedrockAmazon S3AWS GlueAmazon RedshiftAmazon EmrAmazon Kinesis

ragai-agentsfine-tuningcloud-architecturemachine-learningdata-engineeringartificial-intelligence

We are seeking an experienced Data and AI Cloud Architect to join our AWS Professional Services team in Taiwan. In this role, you will work directly with enterprise customers — particularly in the manufacturing and semiconductor industries — to design and implement modern data platforms, analytics solutions, and AI/ML workloads on AWS. You will serve as a trusted technical advisor, helping customers accelerate their cloud adoption journey and unlock business value from their data assets.

Key job responsibilities
Key Responsibilities

- 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
- 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)
- 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)
- Collaborate with customers' technical and business stakeholders to define data strategies, roadmaps, and governance frameworks
- Lead technical workstreams within ProServe engagements, mentoring junior architects and consultants
- Develop reusable assets, frameworks, and best practices for Data & AI solution delivery within the manufacturing and semiconductor domains
- Partner with AWS account teams, solution architects, and specialist teams to identify and shape new customer opportunities
- Contribute to thought leadership through whitepapers, blog posts, reference architectures, and customer presentations
- Stay current with emerging AWS services and industry trends in data engineering, analytics, and generative AI

About the team
AWS Professional Services works with enterprise customers and partners to help them realize their desired business outcomes through cloud adoption. Our team assists customers in achieving the greatest value from AWS by providing guidance, best practices, and hands-on delivery support throughout their cloud journey.

Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Inclusive Team Culture
AWS values curiosity and connection. Our employee-led and company-sponsored affinity groups promote inclusion and empower our people to take pride in what makes us unique. Our inclusion events foster stronger, more collaborative teams. Our continual innovation is fueled by the bold ideas, fresh perspectives, and passionate voices our teams bring to everything we do.

Mentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

Basic qualifications

- Experience conveying complex technical concepts to both technical and business audiences
- Bachelor's degree or above in computer science, computer engineering, or related field, or Bachelor's degree and 1+ years of data scientist or similar role involving data extraction, analysis, statistical modeling and communication experience
- 8+ years of experience in data engineering, data architecture, or cloud architecture, with 5+ years hands-on designing and implementing data solutions on AWS or other major cloud platforms
- Deep expertise in data platform technologies: data lakes, data warehouses, ETL/ELT pipelines, streaming architectures, and data governance, with proficiency in Python, SQL, Spark, or Scala
- Fluency in Mandarin Chinese and English (written and verbal)

Preferred qualifications

- Experience with large scale IT/digital/business transformation or migration programs in a customer facing role
- Domain expertise in manufacturing and/or semiconductor industries — understanding of fab operations, MES/ERP integration, equipment health monitoring, yield management, process control (SPC/FDC), supply chain digitization, and semiconductor-specific data challenges (high-volume time-series data, wafer-level analytics, APC, predictive maintenance)
- Experience with Industry 4.0 / Smart Manufacturing initiatives including IoT, digital twin, edge-to-cloud architectures, and OT/IT convergence for industrial data integration
- Experience with generative AI architectures including RAG patterns, foundation model fine-tuning, and AI agents
- Familiarity with data privacy and compliance requirements in the Taiwan market

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

How we rate this

Data and AI Architect , Professional Services - Taiwan at Amazon rates 75 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Data and AI Architect , Professional Services - Taiwan is an open job at Amazon.
Level rates this role AI Level 3 of 4: Works on AI.
The role is based in TW, TPE, Taipei.
The job was posted on June 15, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGAI agentsFine-tuningCloud ArchitectureMachine learningData EngineeringArtificial IntelligenceBedrock

Questions you could be asked

How would you design a retrieval step so the model answers from real data instead of guessing?
How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through fine-tuning a model: what data did you use, and how did you check the result?
Tell me about a project where cloud architecture was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: RAG, AI agents, Fine-tuning, Cloud Architecture, and Machine learning. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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