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Staff Engineer, Experience Engineering

LaunchDarkly - Remote - Remote - posted 2026-08-20

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Salary: USD 182,600 - 295,350 / annual

LaunchDarkly is seeking a Staff Engineer to design and build the next generation of user experiences across their product suite. The role focuses on the Experience Engineering team, which is responsible for helping all LaunchDarkly users (human and agent) interact with and leverage the platform's feature management, A/B testing, and observability capabilities. You will work across LaunchDarkly's entire product suite, understanding key use cases and building experiences and technical platforms that enable other teams to ship better user experiences faster. The company has learned through extensive user research and observability that a major redesign can significantly improve user productivity and satisfaction. Key responsibilities include: designing and building next-generation user experiences for both human and AI agent users; collaborating with product teams to provide tools and platforms for building great experiences; mentoring engineers and raising the bar for technical rigor and system design; and owning operational excellence for the experience platform including monitoring, observability, incident response, and on-call duties. Required qualifications: 10+ years building large-scale products for sophisticated audiences; experience designing interfaces and supporting technology platforms in enterprise applications; technical leadership skills including setting direction, writing specs, and influencing across teams; BA/BS in mathematics, statistics, data science, or related field (graduate degree preferred). Desired experience includes: Go, Python, or similar languages; event-driven architectures and large-scale data processing; cloud environments (AWS, GCP) and data stores (ClickHouse, Redis, DynamoDB, Kafka); experiment lifecycle tooling and flag-experiment integration; familiarity with competitive products (Statsig, Eppo, GrowthBook, Optimizely); funnel analysis, causal inference, or Bayesian experimentation.

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