Amazon
Senior Worldwide Specialist Solutions Architect - GenAI, Data & AI GTM
Amazon, Seattle, Washington, us, 98127
Overview
Senior Worldwide Specialist Solutions Architect - GenAI, Data & AI GTM Role description: You will help some of our largest customers build and deploy GenAI enabled applications using Amazon Bedrock, Bedrock AgentCore, and Strands. You will engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services. AWS is looking for a Generative AI Solutions Architect to help customers operationalize generative AI agentic workflows at scale, collaborating with service teams to drive product roadmaps and deliver technical guidance through white papers, architecture blogs, and GitHub samples. Travel up to 30% may be possible. Responsibilities
Customer Advisor - Implement, and deploy state of the art GenAI solutions. Build prototypes, PoCs, and explore new solutions. Interact closely with customers. Thought Leadership Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events. Partner with Data Scientists, SAs, Sales, Business Development and the Gen AI Service teams to accelerate customer adoption and provide guidance on engagements. Act as a technical liaison between customers and the AWS GenAI services teams to provide customer-driven product improvement feedback. Develop and support an internal AWS community of GenAI subject matter experts; create field enablement materials to help teams integrate AWS GenAI solutions into customer architectures. Basic Qualifications
3+ years of experience in end-to-end technical architecture, design, deployment and operations for GenAI/ML platforms and applications. 3+ years of experience with large language models including LLM architectures, model evaluation, adapters, and customization (pre-training and fine-tuning). Experience with Agentic infrastructure frameworks such as Bedrock AgentCore or similar platforms; migration between agent runtimes. 2+ years of experience with identity and credential management for AI agents and automated workloads. Experience with orchestration frameworks such as CrewAI, LangGraph, LLAMA Index, AutoGen, etc. Proficient with design, deployment, and evaluation of LLM-powered agents and orchestration approaches. 8+ years of experience in technology domains such as software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics. Masters degree in statistics, mathematics, data science, business analytics, engineering, or computer science. Preferred Qualifications
Agent communication protocols: MCP, A2A, and multi-vendor agent interoperability. Technical thought leadership: Blogs, conferences, GitHub contributions, or research on agentic AI and enterprise automation. Multimodal agent development: Vision, audio, code interpretation, and complex reasoning workflows in production. Experience with Container Platforms (Docker, Kubernetes/Fargate). Experience with performance benchmarking and providing guidance on building, deploying and monitoring ML models on AWS at scale. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require a workplace accommodation during the application or hiring process, please visit amazon.jobs accommodations for more information. Our compensation reflects the cost of labor across several US geographic markets. The base pay range for this position is described in company information. This position will remain posted until filled. Applicants should apply via our internal or external career site. Company
Amazon Web Services, Inc. #J-18808-Ljbffr
Senior Worldwide Specialist Solutions Architect - GenAI, Data & AI GTM Role description: You will help some of our largest customers build and deploy GenAI enabled applications using Amazon Bedrock, Bedrock AgentCore, and Strands. You will engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services. AWS is looking for a Generative AI Solutions Architect to help customers operationalize generative AI agentic workflows at scale, collaborating with service teams to drive product roadmaps and deliver technical guidance through white papers, architecture blogs, and GitHub samples. Travel up to 30% may be possible. Responsibilities
Customer Advisor - Implement, and deploy state of the art GenAI solutions. Build prototypes, PoCs, and explore new solutions. Interact closely with customers. Thought Leadership Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events. Partner with Data Scientists, SAs, Sales, Business Development and the Gen AI Service teams to accelerate customer adoption and provide guidance on engagements. Act as a technical liaison between customers and the AWS GenAI services teams to provide customer-driven product improvement feedback. Develop and support an internal AWS community of GenAI subject matter experts; create field enablement materials to help teams integrate AWS GenAI solutions into customer architectures. Basic Qualifications
3+ years of experience in end-to-end technical architecture, design, deployment and operations for GenAI/ML platforms and applications. 3+ years of experience with large language models including LLM architectures, model evaluation, adapters, and customization (pre-training and fine-tuning). Experience with Agentic infrastructure frameworks such as Bedrock AgentCore or similar platforms; migration between agent runtimes. 2+ years of experience with identity and credential management for AI agents and automated workloads. Experience with orchestration frameworks such as CrewAI, LangGraph, LLAMA Index, AutoGen, etc. Proficient with design, deployment, and evaluation of LLM-powered agents and orchestration approaches. 8+ years of experience in technology domains such as software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics. Masters degree in statistics, mathematics, data science, business analytics, engineering, or computer science. Preferred Qualifications
Agent communication protocols: MCP, A2A, and multi-vendor agent interoperability. Technical thought leadership: Blogs, conferences, GitHub contributions, or research on agentic AI and enterprise automation. Multimodal agent development: Vision, audio, code interpretation, and complex reasoning workflows in production. Experience with Container Platforms (Docker, Kubernetes/Fargate). Experience with performance benchmarking and providing guidance on building, deploying and monitoring ML models on AWS at scale. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. If you require a workplace accommodation during the application or hiring process, please visit amazon.jobs accommodations for more information. Our compensation reflects the cost of labor across several US geographic markets. The base pay range for this position is described in company information. This position will remain posted until filled. Applicants should apply via our internal or external career site. Company
Amazon Web Services, Inc. #J-18808-Ljbffr