Senior Solutions Architect - GenAI and Machine Learning, AGS US Specialist SA

Senior Solutions Architect - GenAI and Machine Learning, AGS US Specialist SA

Job ID: 2935611 | Amazon Web Services, Inc. AWS GenAI/ML Specialist Solutions Architects (SSAs) are technologists with deep domain-specific expertise, able to address advanced concepts and feature designs. As part of the AWS sales organization, SSAs work with customers who have complex challenges that require expert-level knowledge to solve. SSAs craft scalable, flexible, and resilient technical architectures that address those challenges. This might involve guiding customers as they refactor an application or designing entirely new cloud-based systems. Do you enjoy solving novel and unique technical challenges for customers? Become an AWS Specialist SA! The GenAI/ML Specialist SA Team is made up of deep domain experts who work directly with our customers to solve their most complex challenges. We are the Generative AI, Traditional AI, and Machine Learning experts for AWS customers and the Account Teams that support them. We contribute to account planning, architecting GenAI and Machine Learning solutions to ground-breaking customer challenges, running Proof-of-Concepts, and trying new things. Our team is at its best when a customer is thinking big and needs specialized experience to innovate for their business. Key job responsibilities

Provide customers with deep technical expertise in Generative AI, Traditional AI, and Machine Learning with AWS products to meet their business objectives. Collaborate with specialist, sales, marketing, and products teams to ideate around your customers’ most challenging problems. Act as a trusted advisor to line of business, AI, Data, and C-suite leaders. Lead architectural reviews and workshops to advance your customer’s technical objectives. Act as a thought leader sharing best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events. Educate customers on the value proposition of AWS, and participate in architectural discussions to ensure solutions are designed for successful deployment in the cloud. Provide data and anecdotes on what is working and what is not back to the larger specialist community and product teams. Act as primary point of contact for urgent customer issues in your technical specialty. Serve as a thought leader in the Generative AI space, representing AWS at industry events and conferences. Develop technical content, workshops, and thought leadership to enable the broader technical community, including Solution Architects, Data Scientists, and Technical Field Community members. We prefer this candidate to have a track record of thought leadership and innovation around Machine Learning, Comfortable presenting to senior data and AI leaders, and have demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment. BASIC QUALIFICATIONS

5+ years of design, implementation, or consulting in applications and infrastructures experience. 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience. 5+ years of technology/software sales experience. Experience with Python to analyze datasets, train, evaluate, deploy, fine-tune, and optimize models. Experience designing, developing, and optimizing high-quality prompts and templates that guide LLM behavior. Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches. 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience. PREFERRED QUALIFICATIONS

Knowledge of AWS services, market segments, customer base and industry verticals. Hands-on experience with Amazon Web Services. Experience delivering analytic solutions for AI workloads. Experience with open source frameworks for building applications powered by language models. Advanced degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science. 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.

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