Lead Product Designer

New Relic New Relic · Enterprise · Hyderabad, India · Developer Tools

Lead Product Designer for New Relic's AI Monitoring team, focusing on designing "APM for AI" to provide end-to-end visibility into AI stacks. The role involves creating complex, information-dense interfaces for telemetry data, rapid prototyping in code-adjacent environments, and designing for trust, confidence levels, and human-in-the-loop patterns for agentic workflows. Requires deep understanding of AI interaction patterns, explainability, evals, prompt engineering, and agentic UX, with strong data visualization and prototyping skills.

What you'd actually do

  1. Lead End-to-End Design: Serve as the product design lead for AI Monitoring, shaping the product strategy and moving the platform in the right direction through high-autonomy and fast iteration.
  2. Design for Complexity: Create information-dense interfaces that make telemetry data—including traces, metrics, logs, and topology maps—legible and actionable for expert users without "dumbing it down".
  3. Rapid Prototyping: Move at engineering speed by building functional demos and interactive prototypes in code-adjacent environments (primarily Claude Code, with familiarity of Cursor, v0, Replit) to communicate vision more effectively than static mocks.
  4. Solve Novel AI Problems: Define how users build trust in AI-generated insights, surface AI confidence levels, and design human-in-the-loop patterns for agentic workflows.
  5. Collaborate and Influence: Co-create with product and engineering partners, proactively managing stakeholder expectations and translating project issues into language they can understand.

Skills

Required

  • Lead-Level Experience
  • Enterprise B2B Expertise
  • AI-Native Fluency
  • Deep understanding of AI interaction patterns
  • explainability
  • evals
  • prompt engineering
  • agentic UX
  • Prototyping Fluency
  • The ability to "build" using modern AI and code-adjacent tools
  • Data Visualization Chops
  • design for information-dense interfaces
  • dashboards, flamegraphs, or topology maps
  • Adaptability
  • operating in high ambiguity and shipping fast to learn
  • User research experience

Nice to have

  • Experience with Model Context Protocol (MCP) server calls and distributed tracing.
  • A portfolio that showcases not just screens, but the clear articulation of design rationale, trade-offs, and system-wide thinking.
  • Familiarity with the New Relic platform or similar APM/Observability solutions.
  • Examples of projects created using AI

What the JD emphasized

  • Lead-Level Experience
  • Enterprise B2B Expertise
  • AI-Native Fluency
  • Deep understanding of AI interaction patterns
  • explainability
  • evals
  • prompt engineering
  • agentic UX
  • Prototyping Fluency
  • The ability to "build" using modern AI and code-adjacent tools
  • Data Visualization Chops
  • Adaptability
  • operating in high ambiguity and shipping fast to learn

Other signals

  • AI Monitoring team
  • APM for AI
  • end-to-end visibility into the AI stack
  • visualizing multi-agent flows
  • making LLM trace data legible
  • designing for progressive autonomy
  • design for complexity
  • information-dense interfaces
  • telemetry data
  • traces, metrics, logs, and topology maps
  • functional demos and interactive prototypes in code-adjacent environments
  • define how users build trust in AI-generated insights
  • surface AI confidence levels
  • design human-in-the-loop patterns for agentic workflows
  • Deep understanding of AI interaction patterns
  • explainability
  • evals
  • prompt engineering
  • agentic UX
  • Prototyping Fluency
  • build using modern AI and code-adjacent tools
  • Data Visualization Chops
  • design for information-dense interfaces
  • dashboards, flamegraphs, or topology maps
  • operating in high ambiguity and shipping fast to learn