Role at a glance
- Salary
- Not Disclosed
- Location
- 센터필드 서관 12층), Seoul, South Korea
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 4+ years
- Education
- Master's, PhD
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Qualifications
Required
- 4+ years of design, implementation, or consulting in applications and infrastructures experience
- Experience implementing AI solutions that can include 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,...
- Hands-on experience with AWS ecosystems (including Bedrock, AgentCore, and SageMaker) to set up secure, private-network AI environments, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector...
- Able 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
Preferred
- Proven ability to lead projects with complex challenges with extensible, operationally excellent, cost optimized, and aligned solutions outcomes
- Ability to lead a team or small organization-wide initiative with business objectives that are partially defined
- Strong ability to determine solution strategy and where to simplify or extend solutions for the best outcome
- Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field, or PhD
- Experience in running & fine-tuning Large and Small Language Models using advanced techniques like LoRA/QLoRA, Instruction Tuning, and RLHF to optimize for specific domain tasks.
- Expertise in architecting AI systems within highly regulated or security-sensitive environments (e.g., Financial Services, Healthcare, Public Sector).
About the role
Original posting provided by 아마존(Amazon)
About the role
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. SSAs craft scalable, flexible, and resilient technical architectures that address those challenges.
What you'll do
• The AI Specialist SA team builds technical relationships with customers of all sizes and operate as their trusted advisor, ensuring they get the most out of the cloud at every stage of their journey while adopting GenAI/ML and Agentic technologies across their organisation.
• You'll manage the overall technical relationship between AWS and our customers, making recommendations on security, cost, performance, reliability and operational efficiency to accelerate their challenging GenAI/ML and Agentic projects.
• Internally, you will be the voice of the customer, sharing their needs with regard to their usage of our services impacting the roadmap of AWS GenAI/ML and Agentic features.
• In this role, your creativity will link technology to tangible solutions, with the opportunity to define cloud-native GenAI/ML and Agentic architectural patterns for a variety of use cases.
• You will participate in the creation and sharing of best practices, technical content and new reference architectures (e.g. white papers, code samples, blog posts) and evangelize and educate about running GenAI/ML and Agentic workloads on AWS technology (e.g. through workshops, user groups, meetups, public speaking, online videos or conferences).
• Technical Leadership & Mentorship: Lead hands-on deep dives and technical workshops, contributing reusable code, reference architectures, and internal technical assets for the broader engineering organization.
Requirements
• 4+ years of design, implementation, or consulting in applications and infrastructures experience
• Experience implementing AI solutions that can include 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, and practical experience implementing Retrieval-Augmented Generation using embeddings, vector stores, and semantic search optimization.
• Able 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
Preferred qualifications
• Proven ability to lead projects with complex challenges with extensible, operationally excellent, cost optimized, and aligned solutions outcomes
• Ability to lead a team or small organization-wide initiative with business objectives that are partially defined
• Strong ability to determine solution strategy and where to simplify or extend solutions for the best outcome
• Master's degree in computer science, mathematics, statistics, machine learning or equivalent quantitative field, or PhD
• Experience in running & fine-tuning Large and Small Language Models using advanced techniques like LoRA/QLoRA, Instruction Tuning, and RLHF to optimize for specific domain tasks.
• Expertise in architecting AI systems within highly regulated or security-sensitive environments (e.g., Financial Services, Healthcare, Public Sector).
Benefits
자세한 사항은 홈페이지 참고
About the company
아마존(Amazon)
독보적인 물류 자동화 인프라와 클라우드 컴퓨팅 기술을 결합하여 고객 중심의 초연결 커머스 생태계를 구축한 글로벌 테크 기업입니다. 이커머스 효율화와 AWS를 통한 IT 인프라 공급에 주력하며, 전 세계 물류와 디지털 서비스의 접근성을 혁신적으로 높이는 데 기여하고 있습니다.