1 day ago
Hanoi, Vietnam or Ho Chi Minh City, VietnamSenior
Responsibilities
- Build trusted technical relationships with customers and advise them on security, cost, performance, reliability, and operational efficiency.
- Design cloud-native architectures and scalable production solutions for GenAI, ML, and agentic workloads.
- Implement AI solutions involving LLMs, multimodal foundation models, fine-tuning, distributed inference, RAG, vector databases, agentic workflows, prompt engineering, and MLOps.
- Capture customer feedback and advocate for AWS roadmap enhancements related to GenAI, ML, and agentic features.
- Create and share technical content, reference architectures, code samples, whitepapers, blog posts, workshops, and educational presentations.
- Lead hands-on technical deep dives and workshops while contributing reusable technical assets and mentoring the broader engineering organization.
Requirements
- 5+ years of experience in the design, implementation, operations, or consulting of distributed applications.
- 3+ years managing technical, enterprise customer-facing resources or equivalent experience.
- 3+ years designing or implementing production AI systems.
- Experience implementing large-scale AI solutions using LLMs or multimodal foundation models, fine-tuning, distributed inference, RAG, foundation-model evaluation, vector databases, agentic workflows, prompt or context engineering, and MLOps.
- Hands-on experience with AWS AI ecosystems, including Bedrock, AgentCore, and SageMaker, and with secure private-network AI environments.
- Practical experience implementing RAG with embeddings, vector stores, and semantic search optimization.
- Strong communication, technical thought leadership, customer influence, solution strategy, and complex-project leadership abilities.
- Preferred qualifications include cloud technology certifications, advanced techniques such as LoRA, QLoRA, instruction tuning, and RLHF, and experience architecting AI systems in regulated or security-sensitive environments.
- A master's degree or PhD in computer science, mathematics, statistics, machine learning, or an equivalent quantitative field is preferred.
Benefits
- AWS provides ongoing mentorship, knowledge sharing, and career-development resources.
- The company promotes inclusive employee-led affinity groups and learning events, including CORE and AmazeCon conferences.
- AWS supports workplace flexibility and work-life harmony.
- Workplace accommodations are available during the application and hiring process.
Tech Stack
Categories
Solutions Engineering
About Amazon
Amazon builds and operates a global e-commerce marketplace, logistics network, and consumer devices, and provides cloud computing via AWS for businesses and developers. The company earns revenue from online retail, third‑party seller services, subscriptions like Prime, advertising, and AWS usage. Founded in 1994 and headquartered in Seattle, it is publicly traded on NASDAQ (AMZN) and serves customers in dozens of countries.