Applied AI Engineer Jobs in Sunnyvale, CA

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.