Principal Applied Scientist, Secure Work Enablement
Core
Define the scientific vision and roadmap for WorkSpaces Advisor, an agentic AI system that autonomously troubleshoots enterprise workspaces and performs multi-step remediation.
Role type
Principal Applied Scientist (Agentic AI / Autonomous Troubleshooting)
Builds
Autonomous agentic reasoning systems, planning/orchestration frameworks, and continuous learning loops for an AI troubleshooting companion.
Domain
Enterprise IT Operations / Cloud Infrastructure / Agentic AI
Deliverable
production ML models
Required skills
Agentic AI reasoning, multi-step workflow orchestration, causal inference, reinforcement learning from human feedback (RLHF), retrieval-augmented generation (RAG), natural language reasoning, evaluation framework design, scientific strategy, mentorship
Preferred skills
Algorithm design and complexity analysis, novel algorithm creation, peer-reviewed scientific contributions in premier journals/conferences
Technologies
Java, C++, Python
Responsibilities
Define the scientific vision and long-term research agenda for agentic troubleshooting; Solve novel, ambiguous research challenges in agentic AI; Align scientific strategy across product, engineering, and business teams; Mentor scientists and engineers; Own the full lifecycle from research to deployment for core intelligence; Contribute to external scientific community via publications and patents.
Seniority
Principal, strategy & mentorship
