As part of the Agentic WorkSpaces organization, we empower millions of professional users—spanning enterprises, research institutions, and government agencies—through AWS WorkSpaces, a cloud-based desktop and application management platform. Our mission is to redefine productivity for users navigating complex legacy application environments by deploying agentic AI solutions that bridge the gap between generative AI and real-world enterprise workflows.
We combine Amazon’s deep operational expertise with a relentless focus on innovation to deliver AI experiences that are intuitive, scalable, and transformative. Where legacy systems pose unique challenges, we become the trusted partner for customers seeking to automate, optimize, and future-proof their workflows.
The Senior Applied Scientist will lead the development of LLM-driven agentic systems tailored to AWS WorkSpaces environments. This role demands pioneering scientific approaches to solve unresolved problems at scale, balancing rapid iteration with rigorous evaluation. Success hinges on your ability to design, implement, and validate AI solutions that empower users to work smarter in legacy-heavy ecosystems.
Key job responsibilities
- Architect agentic AI systems that leverage LLMs, computer vision, and computer-use techniques to interact with legacy applications within AWS WorkSpaces.
- Build evaluation frameworks to quantify agent performance, reliability, and user impact in real-world, unstructured environments.
- Fine-tune and deploy domain-specific LLMs for workspace use cases, ensuring efficiency, safety, and alignment with enterprise requirements.
- Collaborate cross-functionally with peer teams (e.g., troubleshooting, onboarding, security) to embed AI capabilities across the WorkSpaces product suite—from strategic visioning to hands-on implementation.
- Drive operational excellence by delivering high-quality, production-ready science components that meet Amazon’s standards for robustness, reproducibility, and scalability.
About the team Agentic WorkSpaces AI is the core science team within the Agentic WorkSpaces organization, dedicated to building LLM-driven agentic solutions that empower AWS WorkSpaces users—particularly in legacy application environments where modern AI struggles. We design, develop, and deploy intelligent agents leveraging LLMs, computer vision, and computer use to automate complex workflows. Collaborating closely with peer teams across troubleshooting, onboarding, and other critical areas, we integrate AI capabilities that enhance the entire WorkSpaces experience. Our work balances rapid innovation with rigorous evaluation and ethical alignment, delivering scalable, enterprise-ready solutions for millions of users worldwide.
About AWS : Diverse Experiences Amazon 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.
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.
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 flexible work hours and arrangements are part of our culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
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 and AmazeCon conferences, inspire us to never stop embracing our uniqueness.
Mentorship and 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.
Basic Qualifications
- 5+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning
Preferred Qualifications
- Expertise in computer vision or computer-use automation (e.g., UI interaction, screen understanding) to tackle unique legacy system challenges.
- Experience fine-tuning LLMs for domain-specific applications, optimizing for efficiency, safety, and enterprise requirements.
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, WA, Seattle - 167,100.00 - 226,100.00 USD annually