Principal Applied Scientist, Secure Work Enablement

We are looking for a Principal Applied Scientist to own and advance the scientific vision for WorkSpaces Advisor — our agentic AI system that serves as an always-on troubleshooting companion for workspace administrators and end users. You will define the technical roadmap that transforms Advisor from a recommendation engine into a fully autonomous agent capable of reasoning across complex system states, orchestrating multi-step remediation workflows, and continuously learning from outcomes.

This is a leadership role requiring someone who can set the scientific direction for agentic AI in the troubleshooting domain, drive breakthroughs in reasoning and planning under uncertainty, and build the ML foundations that make Advisor the most trusted AI companion in enterprise workspace management.

You'll define and drive the scientific strategy for Advisor's agentic capabilities, establishing the research agenda that keeps us at the frontier of autonomous troubleshooting and self-healing systems.

Architect agentic reasoning systems that enable Advisor to autonomously diagnose root causes across complex, multi-signal environments — correlating performance telemetry, session behavior, network conditions, and infrastructure state to identify problems before users feel them.

Design and build planning and orchestration frameworks that allow Advisor to compose multi-step remediation actions, reason about dependencies and risks, and execute recovery workflows with appropriate human-in-the-loop guardrails.

Develop advanced causal inference models that move beyond correlation to true root-cause identification, enabling Advisor to distinguish symptoms from underlying issues across interconnected system layers.

Build continuous learning systems where Advisor improves from every interaction — leveraging reinforcement learning from human feedback (RLHF), outcome-driven reward signals, and retrieval-augmented generation (RAG) to expand its troubleshooting knowledge over time.

Pioneer natural language reasoning capabilities that allow Advisor to explain its diagnostic process, communicate findings clearly to administrators, and engage in collaborative problem-solving dialogue.

Establish evaluation frameworks and safety mechanisms that ensure Advisor's autonomous actions maintain customer trust — defining confidence thresholds, escalation policies, and rollback strategies for automated remediation.

Influence the broader organization's AI strategy by identifying opportunities to extend Advisor's agentic patterns to adjacent problem spaces, and by publishing findings that advance the state of the art in autonomous IT operations.