Sr Worldwide Specialist - GenAI, SageMaker AI
Amazon.com
Are you energized to drive adoption of generative AI capabilities at AWS customers and AWS service evolution of these technologies with AWS Service leadership? Are you passionate about helping customers operationalize GenAI and ML in their businesses? AWS is seeking a Go-To-Market (GTM) Specialist to define, build and lead the business development efforts to scale world-wide adoption of key MLOps and GenAIOps components of Amazon SageMaker AI. As a world-wide AI/ML Specialist you will be responsible for defining, building and executing targeted initiatives to accelerate worldwide adoption of Amazon SageMaker AI at customers looking to operationalize GenAI workloads in production.
Key job responsibilities
Be the outward face of AWS generative AI and machine learning by defining and executing go-to-market initiatives for Amazon SageMaker AI. As a world-wide AI/ML Specialist, you will be working hand-in-hand with AWS generative AI and machine learning Solution Architects, Product Managers and Marketing Managers to run world-wide initiatives for adoption of AWS built and 3rd party ISV, and open source components for implementing end-end Machine Learning and GenAI workflows and user journeys, from experimentation to production and lifecycle management. Your work will define and drive the process that regional AI/ML presales and account teams will follow to accelerate adoption of SageMaker AI and you will synthesize data and information gathered from customers into your GTM strategy to iteratively scale service adoption. This entails garnering impactful customer and market insights, developing messaging and solution strategies, communicating those findings to product and sales teams, including senior management. This also involves educating and enabling regional AI/ML presales and AWS account teams to drive initiatives to accelerate worldwide adoption of Amazon SageMaker AI.
The candidate will possess outbound product management and/or technical business development experience in positioning and driving adoption of machine learning, deep learning, or generative AI solutions across full lifecycle of iterative model development, deployment and operations commonly referred to as MLOps and GenAIOps. They will have experience in driving engagements and interactions directly with customers at the highest levels of large enterprises and technology ISV partners. The candidate will have technical knowledge and business experience to communicate the benefits of using managed ML and GenAI services in AWS to ML platform engineering, data science and business intelligence teams with Directors, VPs of these teams and with C-Level executives. They will have used this background to launch and drive scale campaigns and initiatives with broader field teams to drive product/solution adoption at scale, ideally in joint collaboration with ISV partners. Additionally, the ideal candidate will have experience in driving adoption and usage of IDEs with a deep understanding of user personas and usability aspects, and a passion for helping customers simplify and implement end-end user journeys through IDE(s). Finally, the candidate will have experience in, and be passionate about helping product teams prioritize roadmaps, guiding marketing teams on messaging, and enabling specialist sellers and field teams on how to position and sell products/services in machine learning, deep learning, or generative AI with strong IDE offerings.
A day in the life
The candidate will drive outbound product management and business development for deep learning and generative AI. They will drive engagements and interactions directly with customers at the highest levels of large enterprises and technology partners. They will utilize their technical knowledge and business experience to guide ML Platform engineering Dirs and VPs at customers through end-end lifecycle journey for GenAI and ML workflows and how AWS 1st party and 3rd party ISV capabilities can be leveraged to accomplish this. They will build internal and external facing assets including video demos, positioning slides, pricing tools, FAQs, enable field AI/ML specialist, partnership and account teams on these assets, conduct customer webinars, working closely with ISV partners, track adoption and revenue trends at key customers/customer cohorts, and device campaigns and initiatives to grow usage and revenue. They will lead weekly calls with Product Managers, Solution Architects, Marketing Managers to discuss revenue and deal pipeline trends, key customer insights, product issues/gaps and discuss roadmap/issue prioritization wrt. integrating with third party ISVs. They will work with account teams and customers to help secure commitment for public references. Finally, they will magnify the impact of their work, by sharing insights with peers and Leadership utilizing Amazon’s business writing practices.
About the team
We are a small world-wide team of Machine Learning, Deep Learning and Generative AI Go-to-Market specialists with a unique blend of product management and technical business development backgrounds, driving global adoption and scaling of Amazon SageMaker as a managed ML and GenAI Service.
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.
Key job responsibilities
Be the outward face of AWS generative AI and machine learning by defining and executing go-to-market initiatives for Amazon SageMaker AI. As a world-wide AI/ML Specialist, you will be working hand-in-hand with AWS generative AI and machine learning Solution Architects, Product Managers and Marketing Managers to run world-wide initiatives for adoption of AWS built and 3rd party ISV, and open source components for implementing end-end Machine Learning and GenAI workflows and user journeys, from experimentation to production and lifecycle management. Your work will define and drive the process that regional AI/ML presales and account teams will follow to accelerate adoption of SageMaker AI and you will synthesize data and information gathered from customers into your GTM strategy to iteratively scale service adoption. This entails garnering impactful customer and market insights, developing messaging and solution strategies, communicating those findings to product and sales teams, including senior management. This also involves educating and enabling regional AI/ML presales and AWS account teams to drive initiatives to accelerate worldwide adoption of Amazon SageMaker AI.
The candidate will possess outbound product management and/or technical business development experience in positioning and driving adoption of machine learning, deep learning, or generative AI solutions across full lifecycle of iterative model development, deployment and operations commonly referred to as MLOps and GenAIOps. They will have experience in driving engagements and interactions directly with customers at the highest levels of large enterprises and technology ISV partners. The candidate will have technical knowledge and business experience to communicate the benefits of using managed ML and GenAI services in AWS to ML platform engineering, data science and business intelligence teams with Directors, VPs of these teams and with C-Level executives. They will have used this background to launch and drive scale campaigns and initiatives with broader field teams to drive product/solution adoption at scale, ideally in joint collaboration with ISV partners. Additionally, the ideal candidate will have experience in driving adoption and usage of IDEs with a deep understanding of user personas and usability aspects, and a passion for helping customers simplify and implement end-end user journeys through IDE(s). Finally, the candidate will have experience in, and be passionate about helping product teams prioritize roadmaps, guiding marketing teams on messaging, and enabling specialist sellers and field teams on how to position and sell products/services in machine learning, deep learning, or generative AI with strong IDE offerings.
A day in the life
The candidate will drive outbound product management and business development for deep learning and generative AI. They will drive engagements and interactions directly with customers at the highest levels of large enterprises and technology partners. They will utilize their technical knowledge and business experience to guide ML Platform engineering Dirs and VPs at customers through end-end lifecycle journey for GenAI and ML workflows and how AWS 1st party and 3rd party ISV capabilities can be leveraged to accomplish this. They will build internal and external facing assets including video demos, positioning slides, pricing tools, FAQs, enable field AI/ML specialist, partnership and account teams on these assets, conduct customer webinars, working closely with ISV partners, track adoption and revenue trends at key customers/customer cohorts, and device campaigns and initiatives to grow usage and revenue. They will lead weekly calls with Product Managers, Solution Architects, Marketing Managers to discuss revenue and deal pipeline trends, key customer insights, product issues/gaps and discuss roadmap/issue prioritization wrt. integrating with third party ISVs. They will work with account teams and customers to help secure commitment for public references. Finally, they will magnify the impact of their work, by sharing insights with peers and Leadership utilizing Amazon’s business writing practices.
About the team
We are a small world-wide team of Machine Learning, Deep Learning and Generative AI Go-to-Market specialists with a unique blend of product management and technical business development backgrounds, driving global adoption and scaling of Amazon SageMaker as a managed ML and GenAI Service.
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.
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