Amazon Web Services (AWS)
Startup Solutions Architect
Amazon Web Services (AWS), San Francisco, California, United States, 94199
Overview
Startup Solutions Architect at Amazon Web Services (AWS). We are looking for technical builders who enjoy working with early stage startups to help them grow, and who have expertise in deep learning, generative AI, and cloud technology. You will work directly with customers to help them design, train, tune, and deploy generative AI models at scale, while leveraging AWS services and best practices. You will spend time with customers, learn new technologies, and contribute to product thinking by advocating for startups with our product teams. You will also share knowledge broadly through technical content and events. Key Responsibilities
Design and implement cloud-native architectures for startup customers Create technical documentation, implementation guides, and customer-facing assets Provide detailed technical guidance on AWS services and best practices Contribute to internal knowledge bases and reusable solution templates Domain Expertise (depth in at least two)
ML/AI Infrastructure: Implement training and inference systems using AWS AI/ML services; Deploy end-to-end ML pipelines using AWS native tools; Optimize model serving architectures for performance and cost Cloud Native & Kubernetes: Design and implement EKS-based solutions and microservices architectures; Apply container security and operational best practices DevOps & Reliability: Implement CI/CD pipelines and IaC solutions using AWS native tools; Apply architectural best practices for high availability and scaling Data Engineering: Design data pipelines and analytics solutions using AWS services; Implement data governance and security controls AWS values diverse experiences. If you do not meet all qualifications, we encourage you to apply. If your career is just starting or includes alternative experiences, don’t let it stop you from applying. Basic Qualifications
5+ years of design, implementation, or consulting in applications and infrastructures 5+ years of experience in at least two technology domains (e.g., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) Technical expertise in at least two domains: ML/AI Infrastructure, Cloud Native & Kubernetes, DevOps & Reliability, or Data Engineering Strong programming skills with proficiency in multiple languages; extensive knowledge of distributed systems, container orchestration, and microservices architecture Demonstrated ability to provide technical leadership through documentation, implementation guidance, and stakeholder engagement Practical experience with ML/AI frameworks, data engineering concepts, and implementing secure, scalable solutions using AWS native tools and services Preferred Qualifications
Experience in software development or Internet-related industries Experience migrating or transforming legacy customer solutions to the cloud Experience working with AWS technologies from a DevOps perspective Amazon is an equal opportunity employer and does not discriminate on the basis of protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you require a workplace accommodation during the application or hiring process, please visit our accommodations information.
#J-18808-Ljbffr
Startup Solutions Architect at Amazon Web Services (AWS). We are looking for technical builders who enjoy working with early stage startups to help them grow, and who have expertise in deep learning, generative AI, and cloud technology. You will work directly with customers to help them design, train, tune, and deploy generative AI models at scale, while leveraging AWS services and best practices. You will spend time with customers, learn new technologies, and contribute to product thinking by advocating for startups with our product teams. You will also share knowledge broadly through technical content and events. Key Responsibilities
Design and implement cloud-native architectures for startup customers Create technical documentation, implementation guides, and customer-facing assets Provide detailed technical guidance on AWS services and best practices Contribute to internal knowledge bases and reusable solution templates Domain Expertise (depth in at least two)
ML/AI Infrastructure: Implement training and inference systems using AWS AI/ML services; Deploy end-to-end ML pipelines using AWS native tools; Optimize model serving architectures for performance and cost Cloud Native & Kubernetes: Design and implement EKS-based solutions and microservices architectures; Apply container security and operational best practices DevOps & Reliability: Implement CI/CD pipelines and IaC solutions using AWS native tools; Apply architectural best practices for high availability and scaling Data Engineering: Design data pipelines and analytics solutions using AWS services; Implement data governance and security controls AWS values diverse experiences. If you do not meet all qualifications, we encourage you to apply. If your career is just starting or includes alternative experiences, don’t let it stop you from applying. Basic Qualifications
5+ years of design, implementation, or consulting in applications and infrastructures 5+ years of experience in at least two technology domains (e.g., software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) Technical expertise in at least two domains: ML/AI Infrastructure, Cloud Native & Kubernetes, DevOps & Reliability, or Data Engineering Strong programming skills with proficiency in multiple languages; extensive knowledge of distributed systems, container orchestration, and microservices architecture Demonstrated ability to provide technical leadership through documentation, implementation guidance, and stakeholder engagement Practical experience with ML/AI frameworks, data engineering concepts, and implementing secure, scalable solutions using AWS native tools and services Preferred Qualifications
Experience in software development or Internet-related industries Experience migrating or transforming legacy customer solutions to the cloud Experience working with AWS technologies from a DevOps perspective Amazon is an equal opportunity employer and does not discriminate on the basis of protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you require a workplace accommodation during the application or hiring process, please visit our accommodations information.
#J-18808-Ljbffr