Senior GENAI Lead

Amazon Web Services (AWS) provides companies of all sizes with an infrastructure web services platform in the cloud ("cloud computing"). With AWS you can requisition compute power, storage, and many other services - gaining access to a suite of elastic IT infrastructure services as your business demands them. AWS is the leading platform for designing and developing applications for the cloud and is growing rapidly with hundreds of thousands of companies in over 190 countries on the platform. AWS Global Services (GS) was formed in early 2022 and is the key "delivery" engine for customer success. We have a vision to provide a seamless combination of technology and human expertise at every phase of the customer cloud adoption lifecycle (train, migrate, build, operate, support, expand), maximizing and accelerating customer success throughout their AWS journey, and thereby creating value for AWS as a whole. Our unique offerings, powered by people and technology, operate across our four primary business units (BUs): 1/ Global Services Security (GSS), 2/ Training and Certification (T&C), 3/ Professional Services (ProServe), and 4/ Support and AWS Managed Services (Support). Together, our teams continuously improve systems, processes, and cross-organization collaboration to deliver better outcomes for both our customers and our employees. It is always Day One on our team, and we believe we exemplify this by maintaining a long-term focus and boldly innovating to meet our customers' needs.

We are seeking an experienced and innovative leader to spearhead our Generative AI initiatives. The Generative AI Leader and Expert will be responsible for driving the development and implementation of cutting-edge generative AI technologies, such as language models, image generation, and audio synthesis. This role requires a deep understanding of the latest advancements in generative AI, as well as the ability to partner with multiples teams of highly skilled researchers and engineers.

Key job responsibilities
- Develop and execute a comprehensive strategy for generative AI research and development initiatives.
- Collaborate with cross-functional teams, including product management, engineering, and data science, to align generative AI efforts with the company's overall goals and objectives.
- Provide thought leadership and guidance on generative AI trends, technologies, and best practices.
- Lead and oversee the research and development of innovative generative AI models, algorithms, and applications.
- Identify and explore new generative AI techniques and methodologies, such as transformer architectures, diffusion models, and generative adversarial networks (GANs).
- Collaborate with data scientists and engineers to ensure the efficient and effective implementation of generative AI solutions.
- Oversee the development and training of large-scale generative AI models, ensuring their accuracy, performance, and scalability.
- Implement effective techniques for model evaluation, bias detection, and mitigation.
- Collaborate with engineering teams to ensure the seamless deployment and integration of generative AI models into various applications and platforms.
- Develop and implement best practices for model management, versioning, and monitoring.
- Provide mentorship and guidance to team members, encouraging their professional growth and development.
- Foster cross-functional collaboration and knowledge sharing across the organization.

About the team
About AWS
Diverse Experiences
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.

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.

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 & 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.

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, there's nothing we can't achieve in the cloud.

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. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.

BASIC QUALIFICATIONS - 3+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
- Bachelors degree in related field or equivalent years of experience
PREFERRED QUALIFICATIONS - Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
- Experience with large scale distributed systems such as Hadoop, Spark etc.
- PhD, or Master's degree and 6+ years of applied research experience

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit This position will remain posted until filled. Applicants should apply via our internal or external career site.

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