PRINCIPAL ARCHITECT

Job Summary

Principal Architect for a multinational organization responsible for designing scalable generative AI platforms using AWS services guiding complex solution architectures and ensuring secure reliable and cost efficient deployments. The role focuses on strategic design technical governance and enabling teams to deliver impactful AI solutions within a hybrid work model.

Responsibilities

• Design end to end generative AI architectures that align with enterprise standards and enable scalable intelligent solutions that address complex business problems across multiple domains.
• Develop robust solution blueprints that integrate generative AI models with existing systems and data pipelines to deliver reliable and reusable AI capabilities.
• Architect cloud native solutions using AWS services with emphasis on CloudFormation templates to ensure consistent automated and compliant infrastructure provisioning.
• Optimize AWS machine learning workflows by defining patterns for training tuning deploying and monitoring models to achieve efficient performance and resource utilization.
• Collaborate with product teams to translate business requirements into detailed technical designs that leverage generative AI and AWS machine learning services in a practical manner.
• Define reference architectures and best practices for generative AI including data preparation model selection prompt design and evaluation to promote high quality outcomes.
• Establish governance for infrastructure as code using CloudFormation to maintain security compliance and configuration consistency across environments.
• Guide teams in adopting secure design principles for AI workloads including data protection access control observability and responsible AI practices.
• Review solution designs and implementation plans to identify risks gaps and optimization opportunities while ensuring adherence to architectural standards.
• Drive performance optimization for AI and machine learning workloads by analyzing usage patterns and recommending improvements in scaling storage and compute strategies.
• Coordinate with platform and operations teams to ensure high availability resilience and disaster recovery readiness for critical AI solutions deployed on AWS.
• Document architectural decisions patterns and guidelines in a clear and reusable manner to support knowledge sharing and onboarding of new team members.
• Engage with stakeholders to communicate architectural options tradeoffs and recommendations that align with organizational strategy and deliver measurable value.
  
  

• Require extensive hands on experience designing and implementing generative AI solutions including model integration prompt engineering and lifecycle management in production environments.
• Require strong proficiency with AWS CloudFormation including authoring modular templates managing stacks and enforcing infrastructure automation practices.
• Require proven expertise with AWS machine learning services such as SageMaker and related tools covering data preparation training deployment and monitoring of models.
• Require solid background in distributed systems microservices and event driven architectures to ensure that AI solutions are scalable secure and maintainable.
• Require demonstrated experience working in hybrid work environments collaborating effectively with distributed teams using remote friendly communication and delivery practices.
• Nice to have prior exposure to MLOps tools and frameworks to streamline continuous integration continuous delivery and monitoring for machine learning and generative AI workflows.
• Nice to have experience with data governance data quality and metadata management practices to ensure that training and inference data used by AI solutions remains trustworthy.
• Nice to have experience mentoring technical teams on AI and cloud architecture topics and contributing to internal communities of practice focused on innovation.
• Nice to have industry knowledge in domains such as finance retail or healthcare which can help shape practical and responsible applications of generative AI.
• Nice to have awareness of ethical AI guidelines and regulatory considerations to ensure that generative AI solutions respect fairness transparency and accountability expectations.