LaunchDarkly helps teams safely manage code and AI agents in production with feature flags, progressive delivery, automated rollback, and runtime control. Backed by Bessemer, Insight and 500 Global.
About the role
Feature management and experimentation have converged into a single market, and the buying dynamic at the top has shifted. Engineering teams are no longer the sole evaluator — data scientists and data-focused PMs now carry equal weight on the largest deals. The bar for statistical depth, warehouse ergonomics, and experiment-first workflows is rising quickly.
What they're looking for
- Senior product leader (GM, VP, or equivalent) with a track record of owning a product line that competes on statistical rigor and data infrastructure
- Has earned credibility with data science leaders and experimentation specialists at sophisticated organizations — and can recruit them
- Has led a function that includes engineering, design, and data science. Comfortable setting a multi-quarter roadmap, championing investment allocation, and reporting results to an executive team and board
- Clear, direct communicator. Decides fast with incomplete information. Prefers shipping and learning to requirements documents
- Opinionated about where experimentation is going in an AI-native world — and specifically, how agents and autonomous systems will use experimentation infrastructure differently than human teams do
More about this role
Feature management and experimentation have converged into a single market, and the buying dynamic at the top has shifted. Engineering teams are no longer the sole evaluator — data scientists and data-focused PMs now carry equal weight on the largest deals. The bar for statistical depth, warehouse ergonomics, and experiment-first workflows is rising quickly.
In traditional experimentation we have built the foundation: a trusted runtime control plane, a growing experimentation engine, and early warehouse-native capabilities. We are winning lower-maturity buyers at healthy rates. We are not yet consistently winning the most sophisticated data organizations. Closing that gap is the job.
In AI experimentation, we have an early lead: the AI-native tooling category has invested in evaluation and conceded production experimentation, and we already have the primitives (statistical significance, multi-armed bandits, experiment-aware guardrails) that no AI-native competitor ships. Extending that lead is the other half of the job.
This leader will own whether LaunchDarkly becomes the definitive experimentation platform in an AI-accelerated world.
- Own the Experimentation pillar. Direct...
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