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LucidLink is scaling to serve larger and more demanding customers. As we do, performance, scalability, and infrastructure efficiency are becoming first-class product capabilities — not just engineering concerns. We’re hiring a Senior Platform Product Manager to own this space. This is a true platform PM role. You’ll work one layer below most user-facing product work, partnering directly with architects and senior engineers to turn deep technical improvements into clear, measurable outcomes for the business and for customers. Consistent with how product management works at LucidLink, this role is outcomes-driven, not feature-driven.
Job Responsibility:
Own a product area covering platform performance, scalability, and (over time) cost efficiency
Partner directly with architects and senior engineers on performance, scalability, and metadata-related initiatives
Turn market and technical insights into prioritized product decisions
Define success metrics and a review cadence to measure platform health and progress
Identify where the platform limits growth today and prioritize work accordingly
Make and communicate explicit tradeoffs between performance, cost, and reliability
Act as the product point of accountability for platform outcomes across Engineering, Product, and GTM
Act as a point of contact for other PMs internally when it comes to performance improvements impacting their domains
Requirements:
Hands-on experience with core platform or infrastructure components
Experience with storage and distributed systems is a plus
Proven ability to work directly with architects and principal engineers as a credible partner and drive meaningful product improvements from ideation to impact
Strong analytical skills
A track record of great trade-off management and clear prioritization under constraints (performance vs cost vs reliability)
Ability to connect technical work to business and customer outcomes, even when impact is indirect
Clear, precise communication of complex technical topics and team priority argumentation
Nice to have:
Background in a technical environment - e.g. as a technical product manager or a software engineer earlier in your career or through formal/informal education
Experience working with enterprise-scale systems or customers
Pragmatic use of AI tools for research, synthesis, and analysis (with sound judgment)