AI Engineer

Artificial Agency is a player-facing agentic AI company for games. The AI Engineer will improve how agents perceive, reason, and act inside games by running experiments, prototyping capabilities, and helping internal teams and customers build integrations with the Behavior Engine.

What you'll do:

• Design and conduct experiments to understand agent capabilities, investigate failures, and compare approaches. Evaluate new features in realistic gameplay and distinguish reliable improvements from one-off successes
• Design and refine perception and function interfaces with game engineers and designers. Make game information, available actions, and action outcomes clear and usable by agents while respecting the intended player experience
• Propose, prototype, and evaluate agent state components and improvements to shared agent systems. Develop capabilities that address game-team and customer needs, working with the Agents and ML teams to turn successful experiments into reusable solutions
• Build and maintain experimental scenarios, scripts, configurations, and analysis tools. Use shared evaluation infrastructure to make experiments repeatable, and work with test engineers to incorporate established scenarios into ongoing coverage
• Teach and advise game technology engineers and designers, Platform, Frontiers (our forward-deployed engineering team), and customers. Review integrations, troubleshoot difficult behaviours, and help teams apply emerging best practices
• Document experimental methods, results, and limitations. Turn findings into practical guidance, examples, and evidence-based recommendations, clearly distinguishing demonstrated capabilities from ideas that need further investigation

What they're looking for:

• An AI-first approach to engineering, with hands-on experience using AI tools for development, testing, debugging, or analysis. You are excited to make AI-driven workflows central to how you work, actively experiment with new capabilities, and adapt your approach as tools improve, while taking responsibility for the quality of what you deliver
• BSc in Computer Science, Software Engineering, or a related field, or equivalent practical experience
• Proficiency in Python, with demonstrated ability to build and debug prototypes, automate experiments, and analyse results
• Practical experience applying machine learning or building AI systems through professional work, research, or substantial projects
• A solid understanding of machine learning fundamentals and experimental methods, including selecting baselines, measuring outcomes, and drawing conclusions supported by evidence
• Strong problem-solving and communication skills, including the ability to investigate unfamiliar systems and explain technical findings to engineers, designers, and customers
• An AI-first approach to engineering: actively using and experimenting with AI tools for development, debugging, and analysis while taking responsibility for the quality of your work
• Familiarity with Unity, Unreal, or comparable game engines is valuable but not required
• An interest in games and how agent behaviour contributes to player experience is important
• An MSc with a focus on artificial intelligence or reinforcement learning is preferred

Benefits:

• Remote possible for exceptional candidates