Generative AI (GenAI) is rapidly growing in importance. We’re seeing more and more amazing Generative AI work being done from AI-beings App and intelligence customer service chatbot to operational data analysis and code generation. Given the scale required for developing generative AI workloads, the cloud is an ideal place to build Generative AI workloads, and Amazon Web Services (AWS) is the leader in the build ofGenerative AI. We’re looking for someone passionate and deeply excited about this space. Someone who is devoted to helping customers understand how Generative AI can make a big difference to their businesses.
As a Generative AI Specialist Solutions Architect (SA) , you will be the Subject Matter Expert (SME) for designing Generative AI solutions that leverage AWS services. As part of the Specialist Solutions Architecture team, you will work closely with other Specialist SAs to enable large-scale customer use cases and drive the adoption of AWS for ML/AI platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers and other companies to fully leverage GenAI on AWS. You will also create field enablement materials for the broader SA population, to help them understand how to integrate AWS ML solutions into customer architectures.
You must have deep technical experience working with technologies related to Large Language Model (LLM),from model fine-tune to prompt engineering. A strong developing machine learning background is preferred, in addition to experience building application and architecture design. You will be familiar with the ecosystem of software vendors in the AI/ML space, and will leverage this knowledge to help AWS customers in their selection process.
Candidates must have great communication skills and be very technical, with the ability to impress AWS customers at any level, from executive to developer. Previous experience with AWS is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior engineers at customers, partners and AWS service teams, influencing their roadmaps and driving innovation.
Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
If you are someone who enjoys innovating, likes solving hard problems and working on the advanced technology, we would love to have you on the team.
Basic qualifications
Expected graduate in 2026 with degree in a highly quantitative field (Computer Science, Machine Learning, Operations Research, Statistics, Mathematics, etc.).
Experience and practice in design/implementation of GenAI solutions.
Experience with LLM related techniques e.g., Prompt Engineering, RAG, Fine-tuning, Agent, Workflow etc.
Experience of GenAI application building, such as technical architecture, design, deployment and operational practice
Open in location of Beijing.
Able to attend 3 months or above offline internship.
26 届毕业生，全日制本科及以上学历
计算机科学、机器学习、运筹学、统计学、数学等研究生学位
设计或实施GenAI解决方案的经验和实践
具有LLM相关技术的经验,例如：提示工程、RAG、微调、代理、工作流等
GenAI应用程序构建的经验，如技术架构、设计、部署和运营实践
工作地点在北京。
可以参加三个月及以上的线下实习
Preferred qualifications
Familiar with different types of prompt design, such as templates, instructions, questions and answers, etc., as well as prompt evaluation methods and tools.
Solid understanding of common machine/deep learning algorithms and hands-on experience in following areas: prompt engineering, BERT, GPT, T5, Transformers.
Large models pretrain/fine-tuning experience, familiar with distributed training.
Experience using Python and/or Java.
Experience with relational databases, No-SQL, and large-scale distributed systems such as Hadoop and Spark.
Past and current experience writing and speaking about complex technical concepts to broad audiences in a simplified format.
Strong written and verbal communication skills.
Experience with and AWS platform (Amazon Bedrock, SageMaker, EMR, Glue, Lambda, EKS, etc.).
熟悉不同类型的提示设计,如模板、说明、问答等,以及提示评估方法和工具
对常见的机器/深度学习算法有坚实的理解,并在以下领域有实践经验:提示工程、BERT、GPT、T5、Transformer
大型模型预训练/微调经验,熟悉分布式训练
使用Python和/或Java的经验
具有关系数据库、NoSQL和大规模分布式系统(如Hadoop和Spark)的经验
过去和现在撰写和向广大受众以简化格式讲解复杂技术概念的经验
出色的书面和口语沟通能力
使用AWS平台(Amazon Bedrock、SageMaker、EMR、Glue、Lambda、EKS等)的经验