AmazonPosted 1w ago

Principal Applied Scientist, WorkSpaces for AI Agents, Applied AI Solutions

Principal Applied Scientist, WorkSpaces for AI Agents, Applied AI Solutions at Amazon scores 89 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

US, WA, Seattleleadfull-time$229k-$309k

AI in this role

bedrocklovable

ai-agents

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
AWS Applied AI Solutions' (AAIS) vision is every business innovating with Amazon AI teammates. Our mission is to build delightful AI solutions that improve human capabilities and business outcomes. The Agentic WorkSpaces organization within AAIS envisions a world where people, teams, and AI collaborate securely from anywhere to create unprecedented value for every organization. We build lovable products that empower every business to unlock the full potential of human-AI teamwork, driving smarter decisions, greater creativity, more value, and faster innovation with confidence.

Amazon Agentic WorkSpaces (AAWS) is building the world's most lovable, secure, and trusted always-on workspace where AI agents and humans work as partners behind enterprise-grade security. Our portfolio spans persistent desktops (Personal), application streaming (Applications), and Core, and is evolving into the governed operating environment for the hybrid workforce: humans get AI-native desktops for their role, and agents get governed desktops scoped to their task, with administrators managing both as one. This surface includes WS4Builders (an AI-native environment for builders) and WorkSpaces for Agents (W4A) — enabling AI agents to work the way humans do, with access to real applications, real interfaces, and real computing environments. Enterprises want to use AI agents for critical business workloads that touch legacy desktop applications and mainframes, yet 75% of organizations run legacy applications that lack modern APIs, and 90% of corporate data remains locked in systems never designed for agents. Agentic WorkSpaces solves this: it gives enterprises a secure, governed environment where agents and humans operate both legacy and modern applications directly, just as an employee would, without costly migrations.

Basic qualifications

- 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

Preferred qualifications

- 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 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.

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AI AgentsBedrockLovable

Questions you could be asked

How do you decide when an AI agent can act on its own versus asking for approval first?
Walk me through how you've used Bedrock in your day-to-day work.
What are the limits of Lovable that you've run into, and how did you work around them?
How would you decide a model or AI system is ready to ship?
Tell me about a time a model underperformed in production. How did you find out, and what did you change?

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