AmazonPosted 3mo ago

AI Strategist, Generative AI Innovation Center

AI Strategist, Generative AI Innovation Center at Amazon scores 69 out of 100 on AI centrality, which makes it AI Level 3 of 4 (Works on AI) on this board. The level measures how much of the work is AI, not seniority.

FR, Courbevoiefull-time

AI in this role

computer-visionnlp

Amazon Web Services (AWS) is looking for experienced and motivated business-oriented technologists who possess a unique balance of business knowledge, effective interpersonal skills, and some technological depth in the following areas: analytics/big data, machine learning and generative artificial intelligence. This role will focus on supporting customers looking to enhance their business or operational outcomes through the use of advanced and emerging technologies.
You will partner with customers, AWS Sales, AWS service teams, AWS industry teams and AWS Professional Services delivery teams to craft industry-specific programs that will serve the needs of the customer, and extend that use to other customers within the industry and related industries. You will leverage and refine a programmatic approach to help customers drive their business metrics across a set of industry-specific needs. As a trusted customer advocate, the Generative AI Strategist will assess and deliver best practices around program delivery, project approaches, and business measurement. The ability to connect business value to a scalable, repeatable, extensible approach is critical to the Strategist role.

Key job responsibilities
• Bring alignment between customer’s technologists and business leads; help them to explore the art of the possible with generative AI and machine learning, and to develop a roadmap to deliver business value in the most effective way
• Discuss complex industry-specific business concepts with executives, line managers and technologists
• Engage with various AWS teams, including applied scientists, solutions architects, business development, marketing, industry specialists, partners and regional organizations
• Drive large, complex sales opportunities from ideation, through vision building and scoping, all the way to closure and into delivery
• Ensure customer success in ideating and deploying proof of concept projects on the AWS platform, and enable them to move forward in learning from the PoC project to deliver production solutions
• Educate customers on the value proposition of AWS and participate in deep business discussions to ensure solutions are designed to capture business value and drive the intended success metrics
• Conduct workshop sessions to identify opportunities with our customers to scope how they could deliver business value through the use of generative AI or machine learning
• Capture and operationalize best-practice knowledge for enterprises that wish to drive generative AI or machine learning more holistically within their operation (e.g., deploying a customer center of excellence)
• Author or otherwise contribute to AWS customer-facing publications such as whitepapers
• Build deep relationships with senior individuals within customers to enable them to be advocates of the industry and advanced technology solutions
• Effectively evangelize and enable various AWS teams to work collaboratively with the Generative AI Innovation Center, including solutions architects, business development, marketing, industry specialists, delivery teams, partners and regional organizations

• Act as a business liaison between customers, services, technologists and support
• Make meaningful contributions to deep business discussions

About the team
Generative AI Innovation Center

What is it?

A program that pairs you with AWS science and strategy experts with deep experience in AI/ML and generative AI techniques to:

Imagine new applications of generative AI to address your needs.
Identify new use cases based on business value.
Integrate Generative AI into your existing applications and workflows.

Who is this for?

Organizations looking for guidance selecting and experimenting with generative AI use cases.
Organizations looking for guidance planning, executing, and securely scaling generative AI use cases.

Why work with the Generative AI Innovation Center?

Identify achievable use cases for generative AI based on your business priorities.
Receive expert guidance to prioritize use cases, estimate business value, assess feasibility and blockers, and define a clear path to success while employing best practices.
Hands-on help developing solutions mapped to requirements, scaling into production, and collaborating closely with stakeholders to share knowledge.

https://aws.amazon.com/generative-ai/innovation-center/

Basic qualifications

- Bachelor's degree, or experience in a professional field or military
- Experience in cloud based solution (AWS or equivalent), system, network and operating system
- Experience in external or internal customer facing, complex and large scale project management
- Bachelor's degree, or several years of professional or military experience
- Several years of technical specialist, design and architecture experience
- Several years of database (eg. SQL, NoSQL, Hadoop, Spark, Kafka, Kinesis) experience
- Several years of consulting, design and implementation of serverless distributed solutions experience
- Several years of software development with object oriented language experience
- Several years of cloud and on-premise integration experience
- Several years of integration, testing and automation experience
- Several years of continuous integration and continuous delivery (CI/CD) experience
- Several years of cloud based solution (AWS or equivalent), system, network and operating system experience
- Several years of external or internal customer facing, complex and large scale project management experience

Preferred qualifications

- Strong organizational skills with an ability to manage numerous demands from internal / external stakeholders and Customers.
- Ability to collaborate with global/enterprise account sales and delivery teams to drive adoption of AI/ML Solutions into top accounts.
- Experience and passion for designing and developing innovative AI/ML solutions that leverage natural language processing, computer vision, statistical learning theory.
- Ability to communicate complex topics to an audience with various functional knowledge, i.e. presentation skills with a high degree of comfort with both large and small audiences.
- High level of comfort communicating effectively across internal and external organizations.
- Ability to think strategically about business, product, and technical problems and develop strategic, baseline, data modeling processes; ability to accurately identify cause-and-effect relationships.

Amazon est un employeur engagé pour l'égalité des chances. Nous sommes convaincus qu'une main d'oeuvre diversifée est essentielle à notre réussite. Nous prenons nos décisions de recrutement en fonction de votre expérience et de vos compétences. Nous apprécions votre envie de découvrir, d'inventer, de simplifier et de construire. La protection de votre vie privée et la sécurité de vos données constituent depuis longtemps une priorité absolue pour Amazon. Veuillez consulter notre Politique de Confidentialité pour en savoir plus sur la façon dont nous collectons, utilisons et traitons les données personnelles de nos candidats.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

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A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Computer VisionNlp

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
Describe a typical day in a role like this one: which parts run through AI directly?
If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

List these exact terms on your resume: Computer Vision and Nlp. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.

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