포지션 상세
Amazon Web Services (AWS) is leading the next phase of AI adoption and is seeking a hands-on AI Specialist Solution Architect (SSA). AWS Specialist Solutions Architects (SSAs) are technologists with deep domain-specific expertise, able to address advanced concepts and feature designs. As part of the AWS sales organization, SSAs work with customers who have complex challenges that require expert-level knowledge to solve. This role focuses on converting AI ambition into programs that can be delivered, operated, and scaled in production environments.
• Manage the overall technical relationship between AWS and customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate GenAI/ML and Agentic projects
• Serve as the voice of the customer internally, sharing their needs regarding AWS GenAI/ML and Agentic features to impact the product roadmap
• Link technology to tangible solutions by defining cloud-native GenAI/ML and Agentic architectural patterns for a variety of use cases
• Participate in the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts)
• Evangelize and educate about running GenAI/ML and Agentic workloads on AWS technology through workshops, user groups, meetups, public speaking, online videos or conferences
• Lead hands-on deep dives and technical workshops, contributing reusable code, reference architectures, and internal technical assets for the broader engineering organization
• 3+ years of design/implementation of production AI systems
• Experience implementing AI solutions including integration of LLMs/multi-modal FMs in large scale systems, fine-tuning LLMs, deployment and distributed inference of LLMs, RAG, FM evaluation, Vector DBs, Agentic workflows, prompt/context engineering, and MLOps
• Hands-on experience with AWS ecosystems (including Bedrock, AgentCore, and SageMaker) to set up secure, private-network AI environments
• Practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic search optimization
• Ability to effectively communicate across an increasing diversity of audiences internally and externally
• Ability to influence customer and internal business decision makers as a technical thought leader
주요업무
• Build technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud while adopting GenAI/ML and Agentic technologies• Manage the overall technical relationship between AWS and customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate GenAI/ML and Agentic projects
• Serve as the voice of the customer internally, sharing their needs regarding AWS GenAI/ML and Agentic features to impact the product roadmap
• Link technology to tangible solutions by defining cloud-native GenAI/ML and Agentic architectural patterns for a variety of use cases
• Participate in the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts)
• Evangelize and educate about running GenAI/ML and Agentic workloads on AWS technology through workshops, user groups, meetups, public speaking, online videos or conferences
• Lead hands-on deep dives and technical workshops, contributing reusable code, reference architectures, and internal technical assets for the broader engineering organization
자격요건
• 4+ years of experience in design, implementation, or consulting in applications and infrastructures• 3+ years of design/implementation of production AI systems
• Experience implementing AI solutions including integration of LLMs/multi-modal FMs in large scale systems, fine-tuning LLMs, deployment and distributed inference of LLMs, RAG, FM evaluation, Vector DBs, Agentic workflows, prompt/context engineering, and MLOps
• Hands-on experience with AWS ecosystems (including Bedrock, AgentCore, and SageMaker) to set up secure, private-network AI environments
• Practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic search optimization
• Ability to effectively communicate across an increasing diversity of audiences internally and externally
• Ability to influence customer and internal business decision makers as a technical thought leader
