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Amazon
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector.
Are you a customer-obsessed builder with a passion for helping customers achieve their full potential? Do you have the business savvy, Generative AI (GenAI) background, and tech 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 Specialist Organization GenAI team as a Specialist Solutions Architect!
Key job responsibilities
Build and maintain technical trusted advisor relationships with influential technical decision makers for the successful adoption and deployment of AWS Gen AI services
Architect solutions leveraging AWS Gen AI services, working with our customers to deeply understand their business needs and to design a technical solution that takes best advantage of the AWS Cloud platform and Gen AI Services.
Thought Leadership – Craft & develop compelling audience-specific messages and tools (product videos, customer success stories, demos, whitepapers, presentations, how to guides etc.) Present AWS services and technologies through forums such as AWS Blogs, Whitepapers, Reference architectures and Public-Speaking events such as AWS Summit and User-Group events. Capture and share best practices and insights internally and with partners and customers.
Develop and support an AWS internal community of AI related Subject Matter Experts
· Collaborate with business development, professional services, training and support teams to help partners and customers learn and effectively use AWS services.
Serve as a key member of the business development and account management team helping to ensure customer success on the AWS platform. Act as a technical liaison between customers, service engineering teams and support. Provide updates on customer progress and ensure plan execution by partners.
About the team
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.
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.
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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
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 (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
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.- Deep experience in design/implementation/consulting experience of Machine Learning/AI/Deep Learning/Gen AI solutions
- Strong understanding and experience in the field of AI and related technologies, including deep learning and overall machine learning concepts. Deep experience developing AI models in real-world environments.
- Strong understanding of Gen AI technologies. Having worked with both structured and unstructured data in the past to gain effective insights.
- Solid grounding in statistics, probability theory, data modelling, machine learning algorithms and software development techniques and languages used to implement analytics solutions
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