Requirements
- Proven background in cloud architecture with direct customer engagement
- Demonstrated hands-on work with AWS in live customer settings
- Solid understanding of current AI and generative AI system designs on AWS
- Skilled at balancing deep technical analysis with clear client communication
- Track record leading technical workshops, discovery calls, deployments, or proof-of-concept initiatives
- Strong decision-making ability in uncertain or evolving situations
- Able to collaborate effectively across sales, implementation, customer support, product teams, and external partners
- Demonstrates proactive responsibility and accountability
Nice to Have
- Delivered generative AI-focused workshops, technical evaluations, or client implementation projects
- Involvement in the AWS Migration Acceleration Program (MAP)
- Built reusable technical resources such as templates, tools, or standardized processes
- Applied Amazon SageMaker in MLOps pipelines, model performance tracking, or deploying custom models
- Exposure to agentic artificial intelligence frameworks
- Production experience using vector databases within RAG-based generative AI systems
- Holds one or more AWS cloud certifications
- Familiarity with cloud cost management, Kubernetes, data pipelines, platform modernization, or related tools
Required (8)
- Proven background in cloud architecture with direct customer engagement
- Demonstrated hands-on work with AWS in live customer settings
- Solid understanding of current AI and generative AI system designs on AWS
- Skilled at balancing deep technical analysis with clear client communication
- Track record leading technical workshops, discovery calls, deployments, or proof-of-concept initiatives
- Strong decision-making ability in uncertain or evolving situations
- Able to collaborate effectively across sales, implementation, customer support, product teams, and external partners
- Demonstrates proactive responsibility and accountability
Preferred (8)
- Delivered generative AI-focused workshops, technical evaluations, or client implementation projects
- Involvement in the AWS Migration Acceleration Program (MAP)
- Built reusable technical resources such as templates, tools, or standardized processes
- Applied Amazon SageMaker in MLOps pipelines, model performance tracking, or deploying custom models
- Exposure to agentic artificial intelligence frameworks
- Production experience using vector databases within RAG-based generative AI systems
- Holds one or more AWS cloud certifications
- Familiarity with cloud cost management, Kubernetes, data pipelines, platform modernization, or related tools
