UX Manager – AI-Native Products

INCEDO

• JOB DESCRIPTION

UX Manager – AI-Native Products (Conversational & Agentic Interfaces )

LEVEL -Manager (player-coach)

TEAM -Products & Platforms

EXPERIENCE 10–14 years

ABOUT THE ROLE

Incedo’s Products & Platforms team builds AI-native products for enterprise clients. Our users ask questions in natural language, review what the AI finds and recommends, and decide what to act on. You’ll set the design direction for that experience and lead a senior UI/UX designer. This is a player-coach role: most of your time goes into hands-on design. WHAT YOU’LL DO

• Set the interaction model for our AI-native products: when to use conversation, when to use structured UI, and how the two combine across dashboards, workspaces and agent workflows.
• Design trust into every AI output, including sources and provenance, confidence and uncertainty, explanations an expert can check, and approval steps before an agent acts.
• Personally own the hardest flows end to end, from research and concepts through prototypes built on live model outputs to shipped product.
• Build and govern the design system, including AI patterns for streaming and partial results, latency, errors and refusals, multi-turn context, undo and handoff to a human.
• Set up a research and quality practice: regular usability testing, feedback loops from real usage, and UX metrics for AI features that guide priorities with product.
• Lead and grow the senior UI/UX designer, set the quality bar and critique practice, partner with product, engineering and data science, and shape the demos we put in front of client executives.

WHAT YOU BRING

• 10–14 years in UI/UX design, including 3+ years leading design for complex B2B or enterprise products, and at least one AI-powered product (assistant, copilot or agent) that you shipped and then improved based on real usage.
• A demonstrated point of view on AI interaction design: when conversation helps and when it gets in the way, how much autonomy an agent should have, and how to show uncertainty without eroding trust.
• Deep conversation design: context across turns, disambiguation, repair when the model misunderstands, and response guidelines for tone, length and structure.
• Agentic and trust patterns for high-stakes work: plan previews, approval gates, undo and rollback, audit trails, and explanations experts can verify quickly.
• Experience measuring AI experiences through task success, time to answer, correction and override rates, and qualitative trust signals.
• Design-system leadership: tokens, components and patterns adopted across multiple products or teams, built to WCAG 2.2 AA by default.
• Senior-level hands-on craft in visual and interaction design for data-dense screens, and in prototyping with live model outputs; expert in Figma or equivalent tools.
• A portfolio of case studies showing framing, trade-offs and outcomes, including what didn’t work and what you changed.