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Razer

Principal Architect Engineer

Razer is hiring a Principal Architect Engineer in Singapore, Singapore. Level rates it ; you can apply on Razer.

Level's read on this job

  • Level rates this role Little AI ●○○○: aI is not part of the work.
  • Level classifies it as a lead role.
  • Level lists 148 other open roles at Razer.

AI in this role

Joining Razer will place you on a global mission to revolutionize the way the world games. Razer is a place to do great work, offering you the opportunity to make an impact globally while working across a global team located across 5 continents. Razer is also a great place to work, providing you the unique, gamer-centric #LifeAtRazer experience that will put you in an accelerated growth, both personally and professionally.

Job Responsibilities :

You will be working with a team of software engineers to architect, build, and deploy containerized and/or serverless applications in the cloud to support Razer's ever-growing ecosystem of microservices, data pipelines, and AI workloads. You will be responsible for the high-level design, architecture, and technical leadership of a scalable, high-performance, cost-effective, secure, and maintainable system that meets both current and future business needs. You will play a critical leadership role in enhancing our existing single-region monolithic system into a distributed, cloud-native microservices architecture - multi-region deployments, data residency compliance, and modern service decomposition.

Essential Roles and Responsibilities

  • Lead the design and evolution of scalable, secure, high-performance, and distributed end-to-end system architectures and robust data synchronization with effective conflict resolution, aligned with business goals and technical standards.
  • Architect and drive the transformation of legacy monolithic systems into modular, domain-driven microservices deployed across multiple geographic regions.
  • Define and implement patterns for regional service deployment, traffic routing, failover, and disaster recovery to achieve low latency and high availability.
  • Design systems that comply with data residency and privacy regulations (e.g., GDPR, PDPA) by ensuring user data is stored and processed within designated geographic boundaries.
  • Utilize containerization and Kubernetes to support scalable and reproducible deployments in a cloud environment (AWS, GCP, or Azure).
  • Collaborate closely with engineering, security, product, operations, and business stakeholders to ensure the architecture supports both functional and regulatory requirements.
  • Define best practices, technical standards, and review processes to ensure consistent and high-quality design and implementation across services and regions.
  • Provide architectural guidance, technical leadership, and mentorship to engineering teams to ensure alignment with architectural vision and system goals.
  • Collaborate with cross-functional teams including PD, internal stakeholders to deliver high-quality solutions.
  • Stay current with emerging technologies in cloud infrastructure, distributed systems, AI/ML, and web architecture, and evaluate their potential to improve the system design.
  • Promote a culture of innovation, technical excellence, and continuous improvement within the architecture and engineering organization.

Pre-Requisites :

Requirements

  • Bachelor's degree in Computer Science, Computer Engineering, or related technical field.
  • 8+ years of software engineering experience, with at least 3+ years in an architecture or technical leadership role.
  • Proven experience in designing and implementing microservices-based architectures in cloud environments (e.g., AWS or GCP).
  • Demonstrated experience with migrating from monolithic to microservices architectures, including service decomposition and integration strategy.
  • Strong understanding of distributed systems, particularly multi-region deployments, including service mesh architectures, traffic routing, global failover strategies, latency optimization, regional scaling, and cross-region consistency.
  • Solid knowledge of data residency and data sovereignty requirements (e.g., GDPR, PDPA, CCPA), and experience designing systems that comply with such regulations.
  • Proficient in cloud-native technologies, including containers (Docker), Kubernetes, CI/CD pipelines.
  • Strong expertise in distributed systems design, CAP theorem trade-offs, event-driven architecture, and eventual consistency models.
  • Excellent communication and stakeholder engagement skills, with the ability to align technical design with business objectives.
  • Ability to produce high-quality architectural documentation, including system diagrams, data flows, and decision records.
  • Familiarity with OAuth 2.0 and OpenID Connect (OIDC) is a plus.
  • Strong understanding of software development principles such as Agile and SCRUM.

Razer is proud to be an Equal Opportunity Employer. We believe that diverse teams drive better ideas, better products, and a stronger culture. We are committed to providing an inclusive, respectful, and fair workplace for every employee across all the countries we operate in. We do not discriminate on the basis of race, ethnicity, colour, nationality, ancestry, religion, age, sex, sexual orientation, gender identity or expression, disability, marital status, or any other characteristic protected under local laws. Where needed, we provide reasonable accommodations - including for disability or religious practices - to ensure every team member can perform and contribute at their best.

Are you game?

How we rate this

Principal Architect Engineer at Razer rates 17 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ 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.

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