Principal Agent Experience Designer

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Agent Experience Designer based in United States.

This is a pioneering principal-level design role focused on defining how AI agents interact with, navigate, and operate complex enterprise software.

• Define and design the machine-operable interface layer that enables AI agents to interact reliably with internal tools, external systems, APIs, and other agents.
• Invent and establish new AX design artifacts, specifications, governance frameworks, operation contracts, behavioral policies, trust specifications, and evaluation criteria.
• Own the end-to-end AX design lifecycle across modeling, contracting, constraining, observing, validating, running, learning, and versioning.
• Establish operability gates for agent workflows, including determinism, safety, observability, recoverability, auditability, and cost awareness.
• Develop evaluation frameworks such as golden tasks, regression suites, and adversarial scenarios to validate agent capabilities and control version changes.
• Design experiences across interactive, supervised, and fully autonomous operating modes, determining appropriate levels of human oversight according to risk and operational context.
• Create dual-layer journey maps that represent human experiences and agent operations in parallel, identifying delegation points, oversight touchpoints, and handoff requirements.
• Define trust and delegation models that clarify when humans interact directly, supervise AI activity, or allow agents to operate autonomously.
• Champion dual legibility so platform elements are understandable to humans while remaining interpretable and actionable by AI agents.
• Influence product vision and organizational strategy around agent readiness, AI-native design, and the evolution from UX and UAX toward AX.
• Establish AX design standards, reusable patterns, best practices, and governance approaches across the broader product development organization.
• Contribute to the evolution of the design system by defining agent-facing components, semantic structures, machine-readable elements, and observability surfaces.
• Partner with Product Management, Engineering, AI/ML, Research, and other stakeholders to ensure agent-oriented designs are technically viable and aligned with product strategy.
• Mentor and guide designers developing expertise in semantic architecture, process modeling, exception handling, agent workflows, and systems-oriented design.
• Help drive the transition from empathy-first interface design toward precision-first approaches centered on process analysis, semantic architecture, and system optimization.

• 7+ years of experience in UX, Product Design, or a related design discipline, with demonstrated progression toward principal-level systems and strategic design work.
• Proven experience designing complex B2B SaaS, enterprise software, platform, or similarly sophisticated products.
• Strong foundation in systems thinking, information architecture, semantic design, and conceptual modeling, with the ability to design structure and logic rather than interfaces alone.
• Experience developing operating models, conceptual frameworks, and system-level design solutions.
• Experience leading cross-functional initiatives involving Product, Engineering, AI/ML, Research, and other technical stakeholders.
• Full understanding of the product design lifecycle, including research, ideation, prototyping, testing, iteration, and delivery within Agile environments.
• Advanced proficiency with modern design and AI-assisted development tools, including Figma, Figma Make, Cursor, Claude Code, and Codex.
• Deep knowledge of agentic logic and orchestration, including LLM interaction patterns such as ReAct and Chain-of-Thought, state machines, tool-use contracts, and autonomous workflows.
• Experience designing for non-deterministic systems, including graceful failure states, AI hallucination scenarios, tool-call errors, handoff protocols, recovery paths, and exception management.
• Strong expertise in semantic modeling and machine-legible information architecture, including concepts relevant to vector embeddings, RAG, typed schemas, and machine-readable structures.
• Ability to design across interactive, supervised, and autonomous operating models while incorporating observability, auditability, safety, and cost considerations.
• Comfortable working with technical artifacts such as API documentation, JSON structures, capability contracts, and system specifications alongside traditional design tools.
• Excellent verbal and written communication skills, with the ability to explain complex agent-system interactions to both technical and non-technical audiences.
• Fluent English communication skills.
• Experience with low-code platforms, software development processes, IDE design, process engineering, service design, operations design, API design, developer experience, or human-AI collaboration is a strong advantage.