GenAI/ML Specialist Solutions Architect, AGS France

AWS Global Sales drives adoption of the AWS cloud worldwide, enabling customers of all sizes to innovate and expand in the cloud. Our team empowers every customer to grow by providing tailored service, unmatched technology, and committed support. We dive deep to understand each customer's unique challenges, then craft innovative solutions that accelerate their success. This customer-first approach is how we built the world's most adopted cloud. Join us and help us grow.

Are you passionate about Artificial Intelligence, Machine Learning, and GenerativeAI? Are you passionate about helping customers build solutions leveraging the state-of-the-art genAI/ML tools on Amazon Web Service (AWS)? Come join us!

At Amazon, we’ve been investing deeply in artificial intelligence for over 20 years, and many of the capabilities customers experience in our products are driven by machine learning. Amazon.com’s recommendations engine is driven by machine learning, as are the paths that optimize robotic picking routes in our fulfillment centers. Our supply chain, forecasting, and capacity planning are also informed by ML algorithms. Alexa is fueled by Natural Language Understanding and Automated Speech Recognition with deep learning; as is Prime Air. We have thousands of engineers at Amazon committed to machine learning and deep learning, and it’s a big part of our heritage.

Within AWS, we’re focused on bringing that knowledge and capability to customers through three layers of the AI stack: 1) Frameworks and Infrastructure with tools like Apache MxNet and TensorFlow, 2) Machine Learning Platforms such as Amazon SageMaker for data scientists, and, 3) API-driven Services like Amazon Bedrock, Amazon Lex, Amazon Kendra, Amazon Transcribe, Amazon Comprehend, and Amazon Rekognition to quickly add intelligence to applications with simple API calls.

AWS is looking for a GenAI/ML Solutions Architect who will be the Subject Matter Expert for helping customers in France design solutions that leverage our GenAI services, including Amazon Bedrock, Amazon SageMaker, and Amazon Q. As part of the team, you will work closely with customers to enable large-scale use cases, design GenAI pipelines, and drive the adoption of AWS for the AI/ML platforms. You will interact with other SAs in the field, providing guidance on their customer engagements, and you will develop white papers, blogs, reference implementations, and presentations to enable customers to fully leverage GenAI on AWS. Additionally, as the voice of the customer, you will work closely with the service teams, and submit product feature requests to drive the platform forward.

You must have deep technical experience working with technologies related to artificial intelligence, machine learning and/or deep learning. A strong mathematics and statistics background is preferred in addition to experience building machine learning models. You will be familiar with the ecosystem of software vendors in the GenAI space, and will leverage this knowledge to help AWS customers in their selection process.

Key job responsibilities
As a GenAI/ML Specialist Solutions Architect, you will:

- Partner with customers' development and data science teams to deeply understand their business objectives, technical requirements, and organizational challenges.
- Design and architect AI/ML solutions that make the best use of the AWS cloud platform; including Amazon SageMaker, Amazon Bedrock, Amazon Comprehend, Amazon Rekognition, Amazon Transcribe, Amazon Lex, Amazon Personalize, and other AWS AI/ML services, to solve real customer problems at scale.
- Accelerate customer adoption and revenue attainment in France by partnering with Solutions Architects, Sales, Business Development, and AWS AI/ML service teams to drive SageMaker and GenAI-related workloads from exploration to production.
- Act as a technical liaison between customers and AWS service teams, channeling customer-driven feedback to influence product roadmaps and continuously raise the bar on service capabilities.
- Evangelize AWS AI/ML services and share best practices through technical content; including AWS blog posts, whitepapers, and reference architectures and public-speaking engagements at AWS Summits, AWS re:Invent, and industry forums.
- Build and nurture an internal community of GenAI subject matter experts in France, enabling knowledge sharing, technical readiness, and a multiplier effect across the region.

About the team
Diverse Experiences

AWS 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.

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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.

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Work/Life Balance

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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
- Bachelor's degree, or MBA in computer science, engineering, analytics, mathematics, statistics, IT or equivalent
- 2+ years experience developing AI models in real-world environments and integrating AI/ML and other AWS services into large-scale production applications.

Preferred Qualifications

- Experience working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage
- Experience working with end user or developer communities
- Experience with Amazon SageMaker AI, Amazon Bedrock and Amazon Kiro
- Experience demonstrating the ability to architect and deliver AI/ML and GenAI solutions using AWS's full stack of AI/ML services

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