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Asmvia Greenhouse

Prinicpal Engineer, Data, BIA & AI - Architect

SingaporePosted 11h ago
OtherLeadFull-time

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About the Role

 

Step into a career with ASM, where cutting edge technology meets collaborative culture.

For over 55 years ASM has been ahead of what’s next, at the forefront of innovation and what’s technologically possible. With more than 4,500 ASMers representing 70 nationalities, our people and our advanced semiconductor devices are playing a crucial role in trends such as 5G, cloud computing, AI, and autonomous driving. But we’re more than just a tech company. We value diversity, inclusion and sustainability as we strive to make a positive impact on the world.  Our development programs help support your growth, shaping your future and pushing the boundaries of innovation to unleash potential.  

Job's mission

ASM is growing rapidly, and the way we work must scale with that ambition. Since our sales, data volumes and operational complexity continue to increase, we cannot simply keep doing the same work in the same way. AI and automation are essential to helping ASM learn faster, make better decisions and grow without multiplying complexity.  

In support of Digital Transformation, the AI Architect will shape how Artificial Intelligence is applied practically and at scale across ASM, connecting business outcomes, end-to-end processes, trusted data, AI solutions and enterprise platforms into a coherent architecture. 

This is a hands-on architecture and solutioning role within ASM’s Global Digital Transformation organization and Data & AI Intelligence capability. The AI Architect will own the enterprise AI architecture and target-state roadmap while working directly with business teams to explore opportunities, select suitable AI capabilities, shape integrated solutions, build prototypes and guide them into production. The role takes an end-to-end view from process opportunity and data readiness through solution and model selection, integration, deployment, adoption, monitoring and measurable impact. 

The AI Architect will assess the current landscape and define a pragmatic plan for where to reuse, integrate, configure, extend, replace or add capabilities. In a later phase, where a clear business case and sufficient data readiness exists, the architect may also evaluate whether an existing model could be adapted and grounded with ASM-specific equipment data. 

 

What you will be working on

Own ASM’s Enterprise AI Architecture 

  • Define ASM’s enterprise AI target architecture, roadmap, standards and reusable solution patterns. 
  • Define how Databricks, Microsoft Copilot, SAP Joule, specialized AI tools and other capabilities fit together, balancing enterprise platforms with justified domain-specific needs. 
  • Design modular, interoperable AI services that can be reused across products and functions, and guide make, buy, integrate and retire decisions. 
  • Establish and maintain an enterprise AI inventory. 
  • Lead AI architecture reviews and maintain alignment with Enterprise Architecture, the Architecture Review Board and ASM’s broader technology roadmap. 

 

Turn AI Opportunities into Working AI Solutions 

  • Work with Business Process Data Owners, Digital Transformation Business Partners and other teams to identify where AI, automation and process redesign can remove friction, increase capacity and deliver measurable outcomes. 
  • Assess process and data readiness for each AI value case, including ownership, standardization, data quality, security and suitability of data. 
  • Advise when to use rules-based automation, Microsoft Copilot, SAP Joule, specialized AI products, AI agents, retrieval-augmented generation, traditional machine learning, or commercially available small, large or multimodal models based on business fit, accuracy, latency, risk and cost. 
  • Translate opportunities into practical solution designs, prototypes and proofs of value; work with AI Engineers, Data Engineers, Data Scientists and other teams to configure AI services, connect enterprise data and systems, validate assumptions and accelerate deployment. 
  • Define reference architectures for AI-enabled solutions, covering Copilots, agent frameworks, retrieval-augmented generation, workflow orchestration, APIs, data access, human oversight and integration with ASM’s digital landscape. 
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