Job description

We are seeking a Principal Applied Scientist to own the scientific vision across Agentic WorkSpaces. This is a foundational role spanning the full portfolio - Personal Applications and Core and the agentic surfaces (WS4Builders and WorkSpaces for Agents). You will define how we measure, improve, and guarantee the performance of AI agents and human-AI teams. A core part of the role is defining the science agenda itself - identifying which problems are most worth solving and where the highest-leverage bets lie. Directions worth exploring might include Organizational Intelligence (turning institutional knowledge into agent-consumable skills) AI Agent Experience / AiAX (agent observability and autonomous remediation) and contextual behavioral security that adapts enforcement in real time for human and agent sessions - but these are illustrative examples not a fixed roadmap and many other directions are possible. You will help define which ones we pursue. The problems you will solve do not have established industry patterns. You will set the direction for the science of how AI agents and people perceive, reason about, and act reliably within computing environments at enterprise scale. Key job responsibilities • Set the long-term scientific vision: Define what best-in-class agent performance evaluation and learning look like across Agentic WorkSpaces - for computer-using agents and human-AI teams alike. Identify the unsolved scientific problems chart a multi-year research roadmap and secure buy-in from VP-level leadership. • Solve highly ambiguous novel problems: Independently frame and deliver solutions to foundational challenges in agent perception, reasoning, evaluation, reliability, and human-AI collaboration - problems where neither the approach nor the success criteria are pre-defined. • Own the evaluation and measurement foundation: Build the benchmarks datasets and metrics that quantify agent and team accuracy, cost, productivity, and safety across the portfolio and diverse enterprise workflows and that gate what we ship. • Drive cross-organizational scientific alignment: Work across partner teams (AgentCore, Bedrock model teams, Identity, Security, the MCP ecosystem) and across the Applied AI Solutions product portfolio to shape how models and agent frameworks are applied and ensure scientific decisions compose into a coherent system. • Deliver measurable business impact: Ensure research translates to customer outcomes: higher task accuracy, lower cost-per-action, faster time-to-production, measurable productivity for human-AI teams and the trust that lets enterprises scale agent workflows. • Raise the scientific bar: Establish rigor in experimentation evaluation and reproducibility. Mentor and grow senior scientists and engineers. Set the standard for applied science quality across the organization. • Advance the state of the art: Contribute to the external technical community through publications patents and open-source contributions that position AWS as the leader in the science of secure agent-computer interaction and human-AI teamwork. About the team 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. 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. 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. 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. 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. - PhD in Computer Science, Machine Learning, or a related field, or a Master's with equivalent applied research experience - 10+ years of applied science experience, including 8+ years applying ML to real-world products at scale - Experience setting research direction and technical strategy across multiple teams and organizations - Deep expertise in modern ML, including LLMs / foundation models, evaluation methodology, and experimental design - Track record of delivering complex, ambiguous research initiatives from concept through production in enterprise environments - Research or applied experience with AI agents, tool use, computer-use / GUI-grounded agents, or autonomous systems - Experience designing benchmarks, evaluation harnesses, and metrics for non-deterministic or agentic systems - Experience with reinforcement learning, imitation / behavior learning, or learning from demonstration - Experience with agent safety, grounding, guardrails, or reliability for LLM-based systems - Familiarity with enterprise constraints: security, auditability, and compliance frameworks (NIST, SOC2, FedRAMP, HIPAA) - Publications, patents, or significant open-source contributions in ML, agents, or AI infrastructure - Experience influencing technical direction at VP+ level in a large technology organization Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. 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 amazon.jobs 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 amazon.jobs . USA, CA, Sunnyvale - 228,700.00 - 309,400.00 USD annually USA, NY, New York - 218,800.00 - 295,900.00 USD annually USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually

Requirements

Must-haves

Key job responsibilities
Raise the scientific bar: Establish rigor in experimentation evaluation and reproducibility. Mentor and grow senior scientists and engineers. Set the standard for applied science quality across the organization.
About the team
PhD in Computer Science, Machine Learning, or a related field, or a Master's with equivalent applied research experience
10+ years of applied science experience, including 8+ years applying ML to real-world products at scale
Experience setting research direction and technical strategy across multiple teams and organizations
Deep expertise in modern ML, including LLMs / foundation models, evaluation methodology, and experimental design
Track record of delivering complex, ambiguous research initiatives from concept through production in enterprise environments
Research or applied experience with AI agents, tool use, computer-use / GUI-grounded agents, or autonomous systems
Experience designing benchmarks, evaluation harnesses, and metrics for non-deterministic or agentic systems
Experience with reinforcement learning, imitation / behavior learning, or learning from demonstration
Experience with agent safety, grounding, guardrails, or reliability for LLM-based systems
Familiarity with enterprise constraints: security, auditability, and compliance frameworks (NIST, SOC2, FedRAMP, HIPAA)
Publications, patents, or significant open-source contributions in ML, agents, or AI infrastructure
Experience influencing technical direction at VP+ level in a large technology organization
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
USA, CA, Sunnyvale - 228,700.00 - 309,400.00 USD annually
USA, NY, New York - 218,800.00 - 295,900.00 USD annually
USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually

Nice-to-haves

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Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

aiawsmachine learningmlllm

Platform: amazon
Effort: medium

Benefits

Benefits detected in the listing.

Health Insurance

Dental

Vision

401(K)

Paid Time Off

Parental Leave