Sr. Specialist Solutions Architect AI/ML, AWS

DESCRIPTION

Are you a customer-obsessed builder with a passion for helping customers achieve their full potential Do you have the business savvy, AI/ML background, and sales skills necessary to help position AWS as the cloud provider of choice for customers Do you love building new strategic and data-driven businesses Join the Worldwide Specialist Organization (WWSO) AI/ML team as a GTM Specialist Solutions Architect!
Key job responsibilities
. Represent the voice of the customer collaborate with field and central teams to bring customer feedback to product teams. Lead curation of custom feature and availability requests for unique customer use cases.
. Provide advanced technical knowledge to your aligned GTM teams to unblock our customers largest and most critical business challenges.
. Along with your extended team, own the technical bar for specialist technical artifacts and standards.
. Collaborate with your GTM colleagues to provide technical insights into GTM strategy and support field marketing to execute local technical events, campaigns, and customer engagements.
. Act as a thought leader sharing best practices through forums such as AWS blogs, whitepapers, reference architectures and public-speaking events such as AWS Summit, AWS re: Invent, etc.
. Guide and Support an AWS internal community of technical subject matter experts aligned to your customers. Create field enablement materials for the broader SA population to help them understand how to integrate new AWS solutions into customer architectures.
A day in the life
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, hasnt followed a traditional path, or includes alternative experiences, dont let it stop you from applying.

Why AWS
Amazon Web Services (AWS) is the worlds most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - thats why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
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, theres nothing we cant achieve in the cloud.
Inclusive Team Culture
Here at AWS, its 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.
Mentorship and Career Growth
Were continuously raising our performance bar as we strive to become Earths Best Employer. Thats why youll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
About the team
The WWSO AI/ML team positions AWS as the best place to run production-quality AI/ML workloads, providing a secure, reliable and scalable infrastructure as well as higher-level services. As a AI/ML GTM Builder, your job will be to create highest-quality go-to-market (GTM) collateral, including customer and internal demos, hands-on labs, workshops, POC accelerators and AWS Solutions. You combine product development skills with agility, ability to build high-quality software that utilizes various aspects of AI and highlights AWS capabilities in this area. You need to be able to learn new concepts and tools quickly and work at all levels of the AI stack, from model building/tuning to applying higher-level AI-powered services to build business applications.

BASIC QUALIFICATIONS

- 7+ years design/implementation/consulting experience of distributed applications

- 5+ years management of technical, customer facing resources
- 5+ years of technical experience in in designing and implementing production AI/ML systems and MLOps pipelines, with hands-on proficiency in frameworks like PyTorch, HuggingFace, Spark, and LangChain
- Technical knowledge of Large Language Models (LLMs), foundation models (FMs), retrieval-augmented generation (RAG), and prompt engineering techniques