Companion Group is a AAA co-development gaming studio with a globally distributed and fully remote setup, renowned for its adeptness in overcoming the most intricate challenges in multiplayer game development.
Our reputation precedes us as an excellent choice for clients aspiring to elevate their latest multiplayer titles, enabling scalability in player numbers, maximising player density, and crafting immersive gameplay experiences.
Embedded seamlessly within a client's in-house team, we collaborate harmoniously to turn dreams into reality. Our portfolio boasts groundbreaking games developed in collaboration with major studios worldwide. As a fully remote studio with colleagues across the globe, we value and emphasise clear, continuous, and transparent communication as highly as technical skills.
As a Senior AI Engineer, you’ll be at the heart of bringing virtual worlds to life by crafting highly believable, complex, and scalable AI systems for multiplayer games. You will work closely with a talented team of developers, designers, and animators to build robust agent decision-making architectures, optimize pathfinding for massive entity counts, and deliver seamless, network-efficient AI behavior. Your expertise will drive critical aspects of our AI technology stack, ensuring players face challenging, immersive, and memorable adversaries and companions.
Architect & Implement: Design, develop, and refine cutting-edge, multiplayer-ready AI frameworks, decision-making systems, and navigation architectures inside and outside of Unreal Engine.
Write Clean Code: Produce elegant, highly efficient, and maintainable C++ code optimized for low-latency and low-CPU overhead.
Optimize Performance: Leverage an expert-level understanding of data structures, algorithmic complexity, and multi-threading to handle high-density AI populations without compromising server framerates.
Collaborate: Partner with cross-functional teams, particularly designers and animators, to build expressive, tactical, and innovative AI behaviors that align with game design pillars.
Network Integration: Contribute to the architecture of server-authoritative AI, optimizing how agent states, sensory data, and movement are replicated across complex multiplayer environments.
Problem Solve: Tackle intricate technical hurdles related to dynamic pathfinding, spatial reasoning, group coordination, and custom steering behaviors in dense, chaotic game worlds.
Qualifications & Technical Skills
Experience: 6+ years of professional game development experience, with a heavy emphasis on core game AI architecture.
Engine Expertise: 4+ years of deep experience within Unreal Engine, specifically working with AI controllers, navigation meshes (NavMesh), and behavior systems.
Proprietary Engines: Experience working with at least one proprietary game engine (utilizing C/C++ OOP or ECS paradigms).
AI Architecture Mastery: Deep understanding of modern game AI methodologies, including Behavior Trees, State Trees, Hierarchical Finite State Machines (HFSM), and Utility AI.
C++ Proficiency: Excellent C++ programming skills, including proficiency in modern standards (C++17 and C++20) applied to performance-critical systems programming.
Multiplayer Awareness: Solid understanding of Client-Server game architecture and how AI processing, physics, and animation budgets behave under server-authoritative setups.
Soft Skills: Excellent communication and collaboration skills, with a proven ability to thrive in a fully remote, globally distributed team.
What Makes You Stand Out
Experience implementing advanced spatial reasoning frameworks, such as Influence Maps, Environment Query System (EQS) overrides, or tactical positioning grids.
Experience with Entity Component Systems (ECS) (e.g., flecs.dev, MassEntity) applied specifically to mass-entity AI and crowd simulation.
Familiarity with Unreal Engine’s Gameplay Abilities System (GAS) and integrating it seamlessly with AI decision-making loops.
Academic or practical exposure to Machine Learning, Reinforcement Learning, or LLM integrations in a gaming context.
Familiarity with scripting languages and tools development (e.g., Lua, Python) for designer-facing AI authoring tools.
Experience with scalable cloud architecture (AWS, Azure, GCP) to support distributed, server-side AI computation.