🤖 Transforming Game Development Through AI 🎮

GameFrame AI is revolutionizing how games are created.   We're not just another AI wrapper; we're architecting the future of creative development

The Challenge: Design and build sophisticated real-time interfaces that seamlessly blend conversational AI with game development workflows, supporting multi-agent coordination, real-time streaming responses, and complex game engine integrations - all while scaling to 1000's of concurrent users

The Role: AI Systems Architect 🚀

As our AI Platform Engineer, you will collaborate with our CTO to architect and build the core AI orchestration layer that powers our revolutionary platform. You'll be designing novel multi-agent systems that understand game development at a semantic level and coordinate complex workflows across distributed VM infrastructure.

You'll work at the intersection of cutting-edge AI research and production-scale systems engineering, building technology that has never existed before: real-time, multi-user AI orchestration for game development.

What You'll Build 🔧

Advanced Multi-Agent Orchestration

• Design and implement LangGraph Swarm architectures with 7+ specialized agents working in concert
• Build custom ReAct agents with sophisticated tool-calling capabilities and error recovery
• Implement constitutional AI layers for safety, consistency, and domain-specific constraints
• Create agent communication protocols for coordinating complex, multi-step game development tasks
• Implement intelligent context management for game development workflows
  
• Create continuous learning systems that improve agent performance through user interactions

Production AI Infrastructure

• Architect multi-provider LLM orchestration (OpenAI, Anthropic, Google) with intelligent fallback and cost optimization
• Build hybrid memory systems combining conversation, entity, and semantic memory with Pinecone vector search
• Implement real-time streaming AI responses integrated with WebSocket infrastructure
• Design distributed agent systems that scale across multiple VM instances and user sessions

Production-Scale Architecture

• Design session routing and VM orchestration for isolating user AI contexts
• Build auto-scaling AI infrastructure that handles traffic spikes while optimizing costs
• Implement comprehensive observability for AI systems with distributed tracing and performance monitoring
• Create robust error handling and failover systems for production reliability

Technical Environment 🛠️

AI/ML Stack

• Core: LangChain, LangGraph, Langsmith, Langfuse
• APIs: LiteLLM, OpenAI/Anthropic/Google
• Memory: Neo4j, Graphiti, Pinecone, Weaviate, Redis, custom embedding systems.
• Frameworks: Custom agent orchestration, constitutional AI layers
• Evaluation: Custom testing frameworks, performance monitoring

Backend Infrastructure

• API: FastAPI, Python 3.11+, async/await patterns
• Database: PostgreSQL 15, TimescaleDB, Redis caching
• Real-time: WebSocket, streaming protocols, pub/sub systems
• Infrastructure: Docker, Kubernetes, AWS/GCP, auto-scaling, tailscale, Portainer, 

Integration Layer

• Game Engines: Unreal Engine, Unity
• VM Orchestration: Custom session routing, multi-user isolation
• Monitoring: Prometheus, Grafana, distributed tracing

Your Technical Expertise 💻

Required: AI/ML Systems Mastery

• 2+ years building production AI systems 
• High-level LangChain/LangGraph experience including custom agents, state machines, memory systems, and chain optimization
• Deep neural network understanding including transformer architectures, attention mechanisms, embedding spaces, and model limitations
• Production RAG systems with advanced chunking strategies, reranking, hybrid search, and context optimization
• Multi-provider LLM integration with experience across OpenAI, Anthropic, Google, and local model orchestration

Required: Backend Systems Engineering

• Expert Python 3.11+ with FastAPI, async/await patterns, and microservices architecture
• Production database systems including PostgreSQL optimization, TimescaleDB, and Redis caching strategies
• Real-time systems with WebSocket management, streaming protocols, and low-latency processing
• Container orchestration with Docker, Kubernetes, and cloud infrastructure (AWS/GCP)
• Distributed systems design patterns, fault tolerance, and observability

Preferred: AI Research & Innovation

• Open-source contributions in AI/ML
• Advanced prompt engineering including few-shot, chain-of-thought, and tree-of-thought techniques
• Evaluation frameworks for automated testing of AI agent performance and prompt regression testing
• Mixture of Experts patterns and agent specialization architectures

Your Impact & Growth 📈

Immediate Impact (First 90 Days)

• Architect core agent systems for Movement and Combat specialists
• Implement multi-provider LLM orchestration with cost optimization
• Build production memory systems with Pinecone integration
• Design evaluation frameworks for agent performance monitoring

Platform Impact (6-12 Months)

• Scale to 500+ concurrent users with auto-scaling infrastructure
• Launch advanced agent capabilities including code generation and semantic understanding
• Implement continuous learning systems that improve through user interactions
• Build enterprise-grade observability and performance optimization

Industry Impact (12+ Months)

• Establish new patterns for AI-driven creative software architecture
• Contribute to open source and research in multi-agent systems
• Scale platform to support thousands of developers creating games
• Lead technical strategy as the platform evolves toward enterprise studios

Benefits 💰

Base Salary commensurate with experience

Equity: Significant equity package with high growth potential

Benefits Package:

• Health, dental, vision with company contribution
• Flexible PTO and remote/hybrid work arrangements
• Professional development budget for AI/ML conferences and research
• Hardware stipend for development equipment and cloud resources
• Research time allocated for staying current with AI developments

Unique Perks:

• Conference speaking opportunities as we establish thought leadership
• Open source contribution time for projects aligned with platform goals
• Direct access to cutting-edge AI models and research partnerships
• Creative project support for personal game development experiments