Job Description
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
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