Sr. Manager, Applied Science, AWS Agentic AI

Amazon Web Services (AWS) is looking for a sr. Manager, Applied to join the Quick Science team. Quick is AWS’s enterprise generative AI assistant that helps users answer questions, summarize documents, generate content, take actions, and automate workflows using information across enterprise systems. As a key member of this team, you will lead research and development efforts in generative AI and Agentic AI to enable intelligent agents that perform complex reasoning, automate multi-step workflows, and make enterprise users significantly more productive.


Key job responsibilities
You’ll work on building and optimizing multi-modal foundation models, training and fine-tuning state-of-the-art LLMs, and architecting systems that scale efficiently across domains. This role blends science leadership, development of applied scientists, innovation, and deep collaboration with engineering teams to bring research into production.

Basic Qualifications

- PhD in Machine Learning, Computer Science, Electrical Engineering, or a related technical field OR a Master’s degree with 5+ years of relevant industry or research experience.
- Industry experience developing machine learning models for real-world applications.
- Experience with generative AI, including model training or building systems with pre-trained foundation models.
- Proven record of peer-reviewed publications or granted patents in AI/ML.
- Proficiency in Python or similar programming languages.
- Experience in at least one of the following areas: natural language processing (NLP), large language models (LLMs), computer vision, or Agentic AI.

Preferred Qualifications

- Experience applying generative AI to enterprise or multi-modal tasks (e.g., code generation, document understanding, or task planning).
- Strong understanding of agentic architectures, autonomous systems, or task orchestration.
- Leadership experience with of science or research teams in scalable ML infrastructure, distributed training, or optimization of large models.
- Deep knowledge of AI safety, hallucination mitigation, or retrieval-augmented generation (RAG).
- Experience mentoring junior scientists and influencing cross-functional stakeholders.
- Ability to think strategically and communicate complex technical topics to non-experts, including senior leadership.
- Track record of shipping scientific innovations into customer-facing products at scale.

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

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.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, NY, New York - 240,600.00 - 325,500.00 USD annually
USA, WA, Seattle - 218,800.00 - 295,900.00 USD annually