Senior Principal Chief Architect - Enterprise AI & Kubernetes

About the role

Red Hat is hiring a Senior Principal Chief Architect for its APAC AI Center of Excellence in Singapore. The role directs the Forward Deployed Engineering (FDE) function, bridging customer production needs with global product and ecosystem engineering hubs, and acts as a trusted advisor to C-level executives in regulated sectors such as financial services, public sector and utilities. It also involves leadership in open-source foundations and regional developer communities.

Key responsibilities

• Lead the FDE squad and own the technical qualification process for regional engagements
• Drive end-to-end strategy for large-scale hybrid cloud AI deployments and define resilient architectural patterns
• Design complex integration layers including identity access management, legacy data pipelines and air-gapped networks
• Act as the technical bridge to global product hubs and coordinate distributed development
• Contribute up to 70% of FDE platform primitives back to upstream open-source communities
• Hold governing, steering or working group roles in foundations such as LF AI & Data and CNCF, and lead APAC meetups and workshops
• Translate telemetry and red-teaming data into insights for global product teams
• Advise regulated industries on compliance, data residency and sovereignty, and build secure on-premises AI stacks with Policy-as-Code
• Lead platform maturity assessments and evolve the SDLC with CI/CD and automated benchmarking
• Mentor senior engineers and principal engineers in the APAC AI CoE

Required profile

• 12+ years in senior technology or architectural leadership, with at least 5 years in financial services, government or other highly regulated sectors
• 5+ years of active participation or leadership in open-source foundations and a track record of building technical communities across APAC
• Ability to influence C-level stakeholders and lead virtual, cross-functional squads without direct authority
• High awareness of sensitive customer data and local compliance laws

Required skills

• Kubernetes-based hybrid cloud platforms, on-premises, public cloud and edge
• System languages such as Go, C/C++ or Python, with open-source contribution history
• Distributed inference, MLOps/LLMOps, model serving and LLM orchestrators (LangChain, LlamaIndex)
• Cloud-native operators, policy engines and data pipeline frameworks
• CUDA, ROCm and GPU/NPU operator management