Game Integrity Engineer · Elysium Interactive

We’re hiring a Game Integrity Engineer to keep our games fair. Cheating in a multiplayer game is an adversarial, moving target — the work sits at the intersection of reverse engineering, detection systems, and data analysis.

What you’ll work on

Detection systems that distinguish legitimate play from automation and cheating, and evolve as the other side does
Reverse engineering cheat tooling and the ecosystems around it to understand what we’re defending against
Monitoring for the game economy and progression — spotting exploits, abuse, and anomalies before they distort the game
Response tooling: investigation, enforcement, and the pipelines that turn raw gameplay data into signals

Who we’re looking for

Solid grasp of data structures & algorithms
Proficient in Java and familiar with JVM internals
Understanding of client-server networking, packet structure, and latency
Minecraft domain knowledge: mechanics, the modding ecosystem, server software (Paper/Folia), protocol internals
Basic Java reversing — able to decompile a .jar and reason about the code (Vineflower, Recaf, etc.)
Fluency working with AI agents: directing them through research, development, and reversing work for real leverage, reviewing their output with a critical eye, and knowing when a problem deserves your own head

Nice-to-haves

Behavioral heuristics for distinguishing human play from automation: timing, pathing, session patterns
Anti-abuse experience: economy monitoring, exploit response, account correlation and evasion tracking
Statistical anomaly detection: modeling expected behavior, outlier analysis, threshold tuning, false-positive discipline
Leveraging LLMs for analysis where traditional methods fall short
JVM bytecode literacy and class file format knowledge
Java instrumentation & runtime hooking (ASM, ByteBuddy, Mixin)
De-obfuscation: name mangling, control flow flattening, string encryption, opaque predicates
Native reversing (Ghidra/IDA) for tooling that lives outside the JVM
ML on player behavior: classifiers, sequence models, feature engineering, adversarial robustness
Stream processing / data pipelines for detection at scale
A past on the other side of this problem: botting, cheat dev, CTFs

Send a resume and, if you have one, something that shows how you think — a write-up, a tool, a project, a CTF solve.