Amazon Sr AI/ML Specialist Solutions Architect Amazon Web Services US SLG & EDU 

United States, Washington, Seattle 

63125172

As a Senior AI/ML Specialist Solutions Architect on the Data and AI team supporting U.S. State and Local Government and Education (SLG/EDU) customers, 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 will play a critical role in helping public sector organizations navigate their AI and generative AI transformation. You will partner with account teams, domain specialists (including those in analytics, databases, storage, and containers), and business development to guide customers in building secure, scalable, and mission-aligned AI/ML solutions. Your focus will include establishing robust MLOps practices and designing enterprise-grade architectures that drive meaningful outcomes for public services, student success, and operational efficiency. In this role, you will also create technical content—such as reference architectures, workshops, and demos—to support customer adoption and enable partners and independent software vendors (ISVs). Additionally, you will help scale impact by developing field-ready enablement materials that empower generalist Solution Architects to incorporate AI/ML and generative AI into their public sector customer engagements.
Key job responsibilities
• Act as a trusted technical advisor to public sector customers in the SLG and EDU space, building strong relationships with technical decision-makers to guide the adoption and deployment of AWS services—particularly around enterprise-grade AI/ML architectures, generative AI solutions, and autonomous agent systems tailored to mission needs in government and education.• Design and architect scalable, secure, and cost-effective AI/ML solutions using AWS’s comprehensive AI stack—from traditional machine learning services to the latest generative AI offerings. Partner closely with SLG/EDU customers to understand their organizational objectives, modernize legacy systems, and ensure solutions meet requirements for security, compliance, governance, and responsible AI.• Serve as a thought leader in the AI/ML and generative AI space for public sector by developing and sharing practical, real-world technical assets. This includes creating reference architectures, workshops, hands-on labs, and demo solutions that showcase modern AI patterns such as LLM integration, retrieval-augmented generation (RAG), autonomous agents, and MLOps tailored for use cases like digital citizen services, student success, and government operations.• Amplify AWS thought leadership by publishing blogs, speaking at public sector events and webinars, contributing to technical communities focused on government and education innovation through AI.
About the team
About AWS
Diverse Experiences
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- 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 8+ years of IT development or implementation/consulting in the software or Internet industries experience
- Minimum of 5 years of experience building production-grade AI systems, including at least 2 years working with modern Generative AI technologies (e.g., LLMs, foundation models, RAG systems) and autonomous agent frameworks.
- At least 4 years of experience implementing AI architecture patterns and MLOps practices, with a minimum of 3 successful deployments of enterprise-grade AI solutions serving 1,000+ users.

- 5+ years of infrastructure architecture, database architecture and networking experience
- Experience with open-source frameworks for building applications powered by language models like LangChain, LlamaIndex, and CrewAI, etc.
- Experience designing, developing, and optimizing prompts and templates that guide LLM behavior.
- Experience with design, deployment, and evaluation of LLM-powered agents and orchestration.
- Advanced degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.