Senior Worldwide Specialist Solutions Architect - Bedrock, Data & AI GTM

About the role

In this role, you will help some of our largest customers build and deploy Generative AI (GenAI) enabled applications using Amazon Bedrock and SageMaker, fine tune and build Generative AI models, and help enterprise customers leverage these models to power end applications. You will engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services.

As part of the Generative AI Worldwide Specialist organization, you will work closely with other Solution Architects from various geographies to enable large-scale customer use cases and drive the adoption of Amazon Web Services for GenAI services. You will interact with other Data Scientists and Solution Architects in the field, providing guidance on their customer engagements. You will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You will also create field enablement materials for the broader technical field population, to help them understand how to integrate AWS Generative AI solutions into customer architectures.

You drive effective feedback gathering from customers, and you distill and translate that feedback into clear business and technical requirements for product and engineering teams to review. Travel up to 30% may be possible.

Responsibilities

• Implement, and deploy state-of-the-art machine learning solutions under GenAI, build prototypes, PoCs, and explore new solutions while interacting closely with customers.
• Advocate for AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures, and public-speaking events (e.g., AWS Summit, AWS re:Invent).
• Partner with Data Scientists, Solution Architects, Sales, Business Development, and the Generative AI Service teams to accelerate customer adoption and provide guidance on their engagements.
• Act as a technical liaison between customers and the AWS Generative AI services teams to provide customer-driven product improvement feedback.
• Develop and support an AWS internal community of GenAI-related subject matter experts worldwide.
• Create field enablement materials for the broader technical population to help them understand how to integrate AWS GenAI solutions into customer architectures.

Requirements

• 4+ years of design, implementation, or consulting in applications and infrastructures experience.
• Experience in professional, non-internship software development, or experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution.
• Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.
• 4+ years of working with Data & AI-related technologies, including AI/ML, GenAI, Analytics, Database, and/or Storage.
• Deep technical experience with large language models (LLMs), including LLM architectures, model evaluation, and fine-tuning techniques.
• Proficiency with design, deployment, and evaluation of LLM-powered agents, tools, and orchestration approaches.
• Experience with embedding model fine-tuning and retrieval method evaluation approaches.
• Understanding of security and compliance requirements for ML/GenAI implementations.
• Experience with LangChain, LLAMAIndex, Data Augmentation, Responsible AI, and Performance Evaluation frameworks.
• Experience architecting end-to-end ML/GenAI applications for customers using AWS services and the Well-Architected Framework.
• Strong communication skills with the ability to engage effectively at all levels, from executives to developers.

Preferred Qualifications

• Experience working with end-user or developer communities.
• Experience with training and deploying machine learning systems to solve large-scale optimizations.
• Experience with distributed computing, programs, and systems.
• Experience communicating with a wide range of stakeholders, including leadership, or experience working with data analytics and using metrics to identify problems.
• Experience with AWS or cloud technologies.
• Experience leading engineering discussions around technology decisions and strategy related to a product.
• Experience in Kubernetes, Docker, or the containers ecosystem.

About the team

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. 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.

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.

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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Pay

The base salary range for this position varies by location:

• San Francisco, CA: $176,600 - $239,000 USD annually
• New York, NY: $169,000 - $228,600 USD annually
• Seattle, WA: $153,600 - $207,800 USD annually

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.

Benefits

• Health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance, and optional supplemental life plans).
• Employee Assistance Program (EAP), Mental Health Support, and 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 amazon.jobs/en/benefits.