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Radio Access Network (RAN) slicing, a key 5G feature, enables different slices (i.e. tenants or applications) to share the same physical network infrastructure while pursuing diverse objectives such as fairness, prioritization, or maximizing throughput. Each slice is allocated a share of radio resource blocks (RBs), which it further schedules among its users as per its own performance objective. In this paper, we identify the unique challenges that arise when performing RAN slicing in today’s multi-cell deployments that require a mechanism for managing interference among cells. We highlight how interference management decisions, that can be easily made in the absence of slicing (where all users share a common objective set by the network operator), become challenging with 5G slicing where we must respect the individual objectives of multiple slices, while retaining performance isolation across slices. We present a system, RadioNinja, that tackles this challenge through a unique decision-making framework that allows different slices to independently contribute towards interference management decisions. RadioNinja further employs a series of techniques to make such decisions within tight RAN scheduling budget of hundreds of microseconds. Trace-driven simulations with real-world channel measurements show that RadioNinja improves slice-level objectives (e.g., throughput, fairness, flow completion times) by 20–60% over state-of-the-art baselines, while consistently meeting sub-millisecond decision deadlines.