Description Are you passionate about Generative AI (GenAI)? Do you want to help define the future of Go to Market (GTM) at AWS using generative AI? In this role, you will play a crucial role in helping customers leverage the power of generative AI to build intelligent applications. Your expertise will be centered on Amazon Bedrock's Knowledge Base feature and Retrieval Augmented Generation (RAG) techniques, enabling organizations to create AI-powered solutions that can access, reason over, and generate responses based on their proprietary data. 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. Key job responsibilities - Customer Advisor- Implement, and deploy state of the art machine learning solutins under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers. - Thought Leadership – Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc. - Partner with Data Scientists, SAs, Sales, Business Development and the Generative AI Service teams to accelerate customer adoption and providing guidance on their customer 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. A day in the life As a GenAI SA at AWS, you'll be the Subject Matter Expert (SME) for helping customers design Generative AI solutions. You'll engage directly with customers to understand their needs, assist in implementation, and deliver briefings. Your role involves creating white papers, blogs, reference implementations, and presentations to enable customers and partners. You'll develop field enablement materials for the broader technical teams to help understand how to integrate AWS GenAI 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. About the team As part of the Generative AI Worldwide Specialist organization, you will work closely with other Machine Learning 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. 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. AWS values diverse experiences. Even if you do not meet all of the 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 - 2+ years of design, implementation, or consulting in applications and infrastructures experience - 4+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience - 5+ years of IT development or implementation/consulting in the software or Internet industries experience - Deep understanding of generative AI, foundation models, and their applications in enterprise settings. - Knowledge of RAG techniques, vector databases, embedding models and prompt engineering. - Proven track record of delivering complex, large-scale AI/ML solutions. - Travel up to 50% may be required. Preferred Qualifications - Knowledge of cloud architecture - Experience with open source frameworks for building applications powered by language models like LangChain, LlamaIndex. - Advanced knowledge of vector databases, semantic and hybrid search technologies, and embedding models. - Expertise in prompt engineering, FM fine-tuning techniques, and model routing strategies. - Familiarity with graph databases and their applications in RAG architectures. - Experience with multimodal AI applications, including text, image, and audio processing. - Knowledge of RAG evaluation metrics and optimization techniques. - Experience with design, deployment, and evaluation of FM-powered agents and tools and orchestration approaches. Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $118,200/year in our lowest geographic market up to $204,300/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other 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.