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

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

Job ID : 3077116 | Amazon Web Services, Inc.

Are you passionate about Machine Learning (ML), Deep Learning, Artificial Intelligence (AI), Generative AI and Agentic AI? Are you excited by the challenge of driving production usage of ML and AI at scale? Come join us!

ML and AI, especially Generative AI and Agentic AI, are rapidly growing in importance. We are witnessing the revolutionary impact of Generative AI creating everything from code to content, while Agentic AI systems are autonomously solving complex business challenges. Given the massive computational scale required for developing AI models, particularly large language models and autonomous agents, the cloud is an ideal place to deploy AI models, and AWS is a leader in this space. We are looking for someone who is passionate about this space and dedicated to helping customers understand how AI can make a big difference to their businesses.

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. You will partner with account teams, domain specialists, 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 outcomes for public services, student success, and operational efficiency. 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 engagements.

You must have deep technical experience across the AI spectrum—from traditional ML and deep learning to Generative AI and Agentic AI—backed by a strong mathematics and statistics foundation. This includes hands-on experience with large language models (LLMs), foundation models, and autonomous agent frameworks, alongside expertise in implementing RAG systems, designing prompt engineering frameworks, and developing multi-agent systems. Proficiency with both commercial and open-source technologies, including LangChain, Hugging Face, PyTorch, vector databases, and embedding models, is required. Your understanding of the AI / ML ecosystem, including leading vendors, emerging startups, and key open-source projects, will be crucial in helping AWS customers create robust ML pipelines, establish effective MLOps practices, and build future-proof AI architectures.

You should be a strong communicator and highly technical, able to engage AWS customers at any level, from executives to developers. Previous experience with AWS is desired but not required, provided you have experience building large-scale solutions. You will work directly with senior engineers at customers, partners and AWS service teams, influencing roadmaps and driving innovation. If you enjoy innovating, solving hard problems, and working with the latest technology, we would love to have you on the team.

Travel up to 30% across the U.S. may be possible.

Key job responsibilities

• Act as a trusted technical advisor to public sector customers in the SLG and EDU space, guiding 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 AI stack. Partner with SLG / EDU customers to understand objectives, modernize legacy systems, and ensure security, compliance, governance, and responsible AI.
• Serve as a thought leader in the AI / ML and generative AI space for the public sector by developing practical technical assets such as reference architectures, workshops, labs, and demos for LLM integration, RAG, autonomous agents, and MLOps for use cases like digital citizen services and government operations.
• Amdify AWS thought leadership by publishing blogs, speaking at events, and contributing to technical communities focused on government and education innovation through AI.

BASIC QUALIFICATIONS

PREFERRED QUALIFICATIONS

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https : / / amazon.jobs / content / en / how-we-hire / accommodations for more information. If the country / region you’re applying in isn’t listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $138,200 / year in our lowest geographic market up to $239,000 / year in our highest geographic market. Pay is based on factors including market location and may vary with knowledge, skills, and experience. Amazon is a total compensation company. Depending on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total package, in addition to a full range of benefits. For more information, please visit https : / / www.aboutamazon.com / workplace / employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.

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Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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