A Hyperscaler cloud architect designs, builds, and manages large-scale AI Native cloud solutions on hyperscale platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP). They leverage the vast, elastic, and globally distributed infrastructure of these providers to develop scalable, resilient, and AI Native applications and services, often focusing on cutting-edge technologies like GenAI, Conventional AI and machine learning.
What you get to do in this role:
- Develop with Java, JavaScript, Python, and other web technologies in order to build scalable, reliable and resilient applications and services that is secure, compliant, fast, and observable.
- Participating in architectural discussions and decision-making processes to ensure alignment with business goals and best practices.
- Documenting architectural designs, configurations, and implementation guidelines for reference and knowledge sharing.
- Build AI-native systems: Use AI-assisted development tools (e.g. Cursor, GitHub Copilot, Windsurf) to architect, code, and scale systems at the core of ServiceNow s cloud.
- Design for agents: Develop distributed systems and APIs that are legible to both human and AI agents, enabling autonomous monitoring, remediation, and scaling.
- Familiarity with the ServiceNow platform (Platform, ITOM, CMDB, Discovery) is a plus
- Build orchestration workflows by leveraging features of the ServiceNow platform.
- Curiosity and a growth mindset, with interest in applying AI to engineering workflows
- Experience in prompt engineering and GenAl is a plus or nice to have.
- Research and implement new open-source and commercial tools, technologies and methodologies.
- Communicate technical decisions (architecture and design) to business and engineering
- Providing mentorship and guidance to junior team members on cloud architecture principles, best practices, and technologies.
To be successful in this role you have:
- Experience in leveraging or critically thinking about how to integrate
AI into work
processes, decision-making, or problem-solving. This may include using AI-powered tools, automating workflows, analyzing AI-driven insights, or exploring AI s potential impact on the function or industry. - 14+ Yrs of Overall experience and at least 5 years in the role of an enterprise architect leveraging cloud computing.
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Proficiency in Java
or another OO language (or) comfort with full-stack development including JavaScript and modern UI frameworks (React, Angular, Vue). -
Strong foundation in distributed systems
, scalable architectures, API design, and infrastructure as code. -
Experience with cloud ecosystems
like AWS, Azure, or GCP, and tools such as Kafka, RabbitMQ, Postgres, MySQL, or equivalent. -
Experience
leveraging or critically evaluating how to integrate AI into work processes, decision-making, or problem-solving. - Has experience operating bare metal Linux servers at scale in a production environment, using configuration management tools such as Puppet, Chef, or Ansible.
- Can research best practices and help maintain and promote high standards for development.
- Has a deep understanding of Linux servers and their components, including networking, storage, and software packaging.
- Can document and communicate systems architecture.
- Ability to design, develop and debug code in a team setting. You should also have experience writing test specifications and test automation.
- Has experience with a variety of open-source tools used in the operation of a production computing environment.
Demonstrated skills in majority of the below areas is essential for this role at the level of an Architect:
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Cloud computing
: - Hyperscaler Cloud Architects should be familiar with different cloud deployment models (public, private, hybrid) and service models (IaaS, PaaS, SaaS) to determine the most suitable architecture in alignment with the organization s direction
- They should have a comprehensive understanding of the various services offered by cloud providers, such as compute instances, storage solutions, databases, networking, analytics, machine learning, and serverless computing.
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Architectural design
- They should be able to apply architectural principles such as scalability, reliability, availability, performance, security, and cost-effectiveness to develop robust cloud solutions. This also calls for familiarity with design patterns specific to cloud computing, such as microservices architecture, serverless computing, event-driven architecture, and distributed systems design.
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Security and compliance
- Cloud architects should be well-versed in cloud security best practices. These include data encryption, secure access management, the least privilege principle, network segmentation, and identity federation. They should know industry-specific compliance requirements such as GDPR, HIPAA, PCI DSS, SOC 2, and ISO 27001 and know how to implement controls to comply with them.
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Containerization and orchestration
- Containerization and orchestration have become integral parts of cloud-native application development and deployment. Cloud architects should have expertise in container technologies like Docker and container orchestration platforms like Kubernetes.
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Scripting and automation
- Automation is vital in managing cloud environments and deploying infrastructure at scale. Cloud architects should be proficient in scripting languages like Python, Bash, or PowerShell to automate routine tasks, deploy infrastructure, and manage cloud resources programmatically.
- They should leverage infrastructure automation frameworks and CI/CD pipelines to automate configuration management, provisioning, and deployment processes, enabling rapid and reliable software delivery in cloud environments.
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Team leadership
- Leadership skills are essential for cloud architects to lead and inspire cross-functional teams and drive successful cloud initiatives. They should be able to mentor and guide team members, foster collaboration, and promote a culture of innovation and continuous improvement.
- Cloud architects must communicate technical concepts effectively, delegate tasks, and empower team members to achieve common goals. They should also demonstrate strong decision-making abilities, prioritize tasks, and manage resources effectively to ensure successful project outcomes.
