AI Engineer

Responsibilities:

AI Model Training & Integration

• Research, design, and integrate advanced AI models-including MCTS and AlphaGo-inspired agents-to predict level difficulty, and evaluate playability.
• Build and maintain gameplay AI agents that can play all levels, enabling automated playtesting, balancing, and progression tuning.
• Develop and optimize AI-driven level generation pipelines, using agent feedback and performance metrics to produce fun, scalable, and high-quality game content.
• Collaborate with game teams to translate AI outputs into actionable improvements that enhance the overall player experience and support data-driven game design.

Workflow Automation

• Collaborate with developers and designers to identify processes that can be optimized or automated.
• Build and maintain efficient pipelines for integrating AI-driven features into development, testing, and deployment.

Tooling & Collaboration

• Work closely with cross-functional teams to implement AI solutions that improve game design, narrative, and overall player experience.
• Communicate AI concepts clearly to technical and non-technical stakeholders.

Continuous Learning & Innovation

• Stay informed about evolving LLM technologies and best practices.
• Experiment with new AI techniques to keep our workflow competitive and cutting-edge.

Qualifications:

• Bachelor’s or Master’s in Computer Science, AI, or a related field (or equivalent experience).
• Reinforcement Learning experience is a plus.
• Proficient in Python and C# or C++.
• Experience with Unity is a plus.
• Solid understanding of LLM fundamentals and how to apply them in real-world scenarios.
• Strong problem-solving abilities and a proactive mindset.
• Excellent communication and collaboration skills.
• A strong passion for gaming and emerging technologies.

Bonus Points

• Gaming industry experience.
• Knowledge of DevOps, CI/CD, and cloud platforms.
• Open-source AI contributions or a robust AI portfolio.