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Strong employer brand, metro location, and lead-level role increase competition, but niche AI-observability specialization reduces applicant pool.
High domain bias due to enterprise observability, AI-native UX, and data-visualization specialization.
Many mandatory specialized skills (lead-level, AI-native, enterprise B2B, prototyping, data-visualization) increase selectivity.
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Lead design strategy and execution for AI Monitoring product, focusing on end-to-end ownership in a complex, emerging product category.
Design information-dense interfaces for telemetry data that support expert users across AI stack layers, enabling actionable insights.
Rapidly prototype interactive functional demos using AI and code-adjacent tools to communicate vision and iterate quickly with engineering.
Proven lead-level product design experience with end-to-end ownership and autonomy in complex problem domains.
Experience designing enterprise B2B infrastructure or developer tools handling large-scale data (thousands of services, millions of data points).
Strong knowledge of AI interaction patterns including explainability, prompt engineering, agentic UX, and AI-native design concepts.
Work Experience Required: Not explicitly mentioned in the JD. Visa sponsorship not available; based in Hyderabad or Bangalore.
Experienced in high-autonomy, fast-iteration environments with engineering-heavy teams, comfortable working with ambiguity.
Expertise in designing complex, information-rich data visualizations like dashboards, flamegraphs, and topology maps for expert users.
Skilled in user research-driven design and applying systems thinking to create consistent product-wide design patterns in enterprise software.