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As an AI/ML Specialist Solutions Architect (SA), you will be the Subject Matter Expert (SME) for designing scalable, secure, and cost-effective AI/ML, Generative AI and Agentic AI solutions that leverage AWS services. Working at the intersection of innovation and enterprise requirements, you'll architect production-grade solutions that are reliable, well-governed, and compliant with industry standards. Your expertise will be crucial in helping organizations build responsible AI practices, from traditional ML to advanced Generative AI and Agentic AI systems, while implementing robust governance frameworks and secure AI pipelines that scale efficiently.AWS Global Services
Key job responsibilities
- Build and maintain technical trusted advisor relationships with influential technical decision-makers to drive successful adoption and deployment of AWS services, with particular focus on enterprise-grade AI/ML architectures, Generative AI solutions, and autonomous agent systems.- Serve as a thought leader in the AI/ML space by developing compelling technical content and practical implementations showcasing modern AI architectures. Create reference architectures, workshops, and demos that highlight integration patterns for LLMs, RAG systems, autonomous agents, and MLOps best practices. Share insights through AWS Blogs, public speaking events, and technical communities.This role can be located in either Singapore, Indonesia, Malaysia, Philippines, Thailand or VietnamAbout the team
Diverse Experiences
Amazon values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.Why AWS
Work/Life BalanceMentorship and Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
- Bachelor's degree in computer science, engineering, mathematics or equivalent
- 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- 10+ years of combined experience in AI/ML and related technologies, with deep expertise in traditional machine learning and deep learning. Must have experience building production-grade AI systems, complemented by practical knowledge of modern Generative AI technologies (LLMs, foundation models, RAG systems) and autonomous agent frameworks. Strong background in AI architecture patterns and MLOps practices, with demonstrated ability to design and deploy enterprise-grade AI solutions at scale.
- Experience in a technical role within a sales organization
- Cloud Technology Certification (such as Solutions Architecture, Cloud Security Professional or Cloud DevOps Engineering)
- Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field, with research or practical experience in emerging AI technologies. Published work or significant contributions to AI/ML open-source projects, particularly in Generative AI or autonomous systems, would be highly valued.
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