About the position
Egofold is an AI initiative within Snail Games focused on building a modular AI “brain” ecosystem for NPC intelligence, real-time perception systems, and simulation tooling across multiple game projects.
We are seeking a senior AI engineer to lead the development of Egofold’s foundational AI systems. This role is responsible for building and structuring a reusable, trainable LLM-based “brain” that can operate across multiple environments and contexts. The focus is on core system design and execution: how the AI reasons, learns, adapts, and integrates training workflows over time.
This is a hands-on role for someone comfortable making technical decisions under ambiguity and operating without fully defined requirements.
Responsibilities
• Design and implement foundational AI systems using large language models as a core reasoning component.
• Architect simulation-based learning systems and training workflows, including fine-tuning, reinforcement learning, evaluation, and feedback loops.
• Build validation, safety, and constraint layers around generative outputs to ensure predictable and controllable behavior.
• Define evaluation frameworks and benchmarking strategies to measure agent performance, stability, and learning progression over time.
• Structure how context, memory, and world state are represented and consumed within the AI architecture.
• Determine how learned behavior, structured logic, and rule-based systems interact within a unified hybrid system.
• Collaborate with engine engineers to integrate AI systems into real-time interactive environments.
• Make system-level technical decisions that prioritize long-term reuse, scalability, and cross-domain adaptability.
Requirements
• Significant professional experience building AI or ML systems beyond simple model or API integration.
• Demonstrated experience working with large language models in a production or applied research context.
• Hands-on experience with agent training methodologies, including reinforcement learning or simulation-based learning systems.
• Strong understanding of training workflows, evaluation strategies, and iterative improvement cycles.
• Strong proficiency in Python and experience integrating AI systems into production environments.
• Ability to reason about complex, stateful systems and learning behavior over time.
• Comfort operating in early-stage, ambiguous environments and taking ownership of foundational systems.
Nice-to-haves
• Experience designing context-aware or agent-based AI systems.
• Background in behavioral AI, simulation, or decision-making systems.
• Familiarity with reinforcement learning, fine-tuning strategies, or hybrid AI architectures.
• Experience integrating AI systems into real-time or interactive environments.
• Familiarity with C++, C#, or Unreal Engine integration workflows.
Benefits
• Operate in a small, high-autonomy team with significant technical ownership and long-term influence.
• True focus on work/life balance
• Paid company holidays, vacation, and separate sick leave
• Medical, dental, vision, and Life/LTD
• 401k with company match