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Generative AI Solutions Architect, AWS Global Government Specialist SA

Amazon is hiring a Generative AI Solutions Architect, AWS Global Government Specialist SA in Arlington, United States. It pays $154k-$208k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

  • On Level's scale, this solutions architect role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting mentions Bedrock, SageMaker and AWS among its tools and skills.
  • Level classes it as a senior role.
  • Amazon has 20,000+ other open roles on Level.

AI in this role

Serve as a Generative AI Specialist Solutions Architect helping government customers design and implement AI solutions on AWS.

BedrockSageMakerAWSMachine learningGenerative AIDeep learning
ai-agentsnlpsolutions-architectureartificial-intelligencecloud-computingtechnical-leadership
Amazon Web Services is seeking a Generative AI Learning Solutions Architect to support our Global Government customers.

Are you excited to help Government customers to leverage generative AI in their missions? Eager to learn from many different enterprise use cases of AWS ML and generative AI? Thrilled to be a key part of Amazon, who has been investing in Machine Learning for decades, pioneering and shaping the world’s AI technology? Come join us!

At Amazon Web Services (AWS), we are helping the federal government build and use AI on the AWS Cloud. We are AI to large volumes of data and against a wide spectrum of problems.

Generative AI is rapidly growing in importance. We’re seeing more and more amazing AI work being done from simple back office applications to complex mission changing agentic workflows. Given the scale required for developing AI models, the cloud is an ideal place to deploy AI models, and Amazon Web Services (AWS) is the leader in the deployment of AI. We’re looking for someone passionate and deeply excited about this space. Someone who is devoted to helping government customers understand how AI can make a big difference to their mission.

This position requires that the candidate selected be a US Citizen and obtain and maintain an active Top Secret security clearance.

Key job responsibilities
As a Machine Learning Specialist Solutions Architect (SA), you will be the Subject Matter Expert (SME) for designing generative AI solutions that leverage AWS services to automate solutions and drive down costs for customers. As part of the Specialist Solutions Architecture team, you will work closely with the other Specialist SAs to enable large-scale customer use cases and drive the adoption of AWS for 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 partners to fully leverage AI on AWS. You will also create field enablement materials for the broader SA population, to help them understand how to integrate AWS AI solutions into customer architectures.

You must have deep technical experience working with technologies related to artificial intelligence, machine learning, deep learning, or generative AI. A strong statistics, mathematics, computer science, or technology background is preferred, in addition to experience helping customers architect enterprise grade AI solutions. You will be familiar with the ecosystem of software vendors in the AI space as well as be able to operate in Python data science environments. You must have the ability to leverage this knowledge to help AWS customers in their software 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.
If you are someone who enjoys innovating, likes solving hard problems and working with innovative technology, we would love to have you on the team.



About the team
About AWS
Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Mentorship 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.

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.

Basic qualifications

- 8+ years of IT development or implementation/consulting in the software or Internet industries experience
- 8+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- 4+ years of design, implementation, or consulting in applications and infrastructures experience
- 2+ years experience in the field of AI, Machine Learning, Deep Learning, NLP and related technologies.
- 2+ years experience developing AI models in real-world environments and integrating AI/ML and other AWS services into large-scale production applications.

Preferred qualifications

- 5+ years of infrastructure architecture, database architecture and networking experience
- Experience working with end user or developer communities
- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
- Experience with Amazon SageMaker AI, Amazon Bedrock and Amazon Kiro
- Experience demonstrating the ability to architect and deliver AI/ML and GenAI solutions using AWS's full stack of AI/ML services

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.



USA, VA, Arlington - 153,600.00 - 207,800.00 USD annually
USA, VA, Herndon - 153,600.00 - 207,800.00 USD annually

How we rate this

Generative AI Solutions Architect, AWS Global Government Specialist SA at Amazon rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agentsNLPSolutions ArchitectureArtificial IntelligenceCloud ComputingTechnical LeadershipBedrockSageMaker

Also common in solutions architect jobs at this level

Pay

This job starts at
$154k
Typical solutions architect job
$169k

This posting starts 9% below the typical solutions architect job. See solutions architect jobs

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. What NLP problem have you worked on, and how did you measure whether it actually worked?
  3. Tell me about a project where solutions architecture was part of your work. What did you do?
  4. Tell me about a project where artificial intelligence was part of your work. What did you do?
  5. Tell me about a project where cloud computing was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: AI agents, NLP, Solutions Architecture, Artificial Intelligence, and Cloud Computing. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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