Senior Applied Scientist, Frontier AI Tooling

Full Job Description

The role will be key to building the products and experiences that will be used by Proserve and Frontier AI organization to deliver business outcomes to our customers

Are you excited about building products that help Proserve and Frontier AI teams understand customer needs, develop the right solutions, and deliver them at scale?

The Frontier AI tooling team is looking for a Senior Applied Scientist to take a high-impact work across our sales and delivery team. Our work spans GenAI agents that answer sales questions in natural language, knowledge graphs, recommendation systems, synthetic controls, account prioritization models, helping proserve delivery consultant accelerate delivery leveraging AI tooling and more. A key part of our effort will be to built a world class context layer that will improve the quality , accuracy , reliability and security of our agents.

As a Senior Applied Scientist, you will own ambiguous, high-value problems end to end, from framing the question with business leaders through to a deployed model that changes how the field operates. You will set technical direction for problems that don't yet have a clear approach, choose the right method rather than the familiar one, and raise the bar for the science across the team. You will partner directly with customers across AWS Sales to understand the challenges they face and deliver solutions they trust and adopt.

You must be an expert in advanced quantitative and machine learning methods, and equally strong at synthesizing and communicating insights to audiences of varying technical sophistication. You will influence decisions well beyond your own projects, and you will help grow the scientists around you through mentorship and technical leadership.

Key job responsibilities

• Own the full lifecycle of complex science problems: problem framing, data exploration, method selection, modeling, evaluation, and production deployment.

• Set technical direction on ambiguous problems and make the design decisions that others build on.

• Partner with business stakeholders across Sales & Delivery consultants to turn open-ended business questions into well-scoped science, and translate results into recommendations leaders act on.

• Raise the scientific bar across the team through design reviews, mentorship, and hands-on guidance.

• Communicate methods, trade-offs, and results clearly to both technical and non-technical audiences.

• Use Python, PySpark, and SQL for data analysis and model development.

About the team 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 empowers us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity, inclusion) 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

• PhD, or Master's degree and 6+ years of building machine learning models for business application experience
• Experience with SQL and Python scripting
• Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
• Experience managing and deploying ML products

Preferred Qualifications

• Experience working with stakeholders, or experience using financial models, KPIs, and data analysis to inform business decisions with proven business impact (e.g., financial savings, operational improvements, or customer benefits)
• PhD or equivalent research experience, or a Master's degree and experience in patents or publications at top-tier peer-reviewed conferences or journals
• Depth in large language models and agentic system
• Experience mentoring or developing other scientists.

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 - 183,800.00 - 248,700.00 USD annually USA, TX, Austin - 167,100.00 - 226,100.00 USD annually USA, VA, Arlington - 167,100.00 - 226,100.00 USD annually USA, WA, Seattle - 167,100.00 - 226,100.00 USD annually

PhD, or Master's degree and 6+ years of building machine learning models for business application experience Experience with SQL and Python scripting Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders Experience managing and deploying ML products