Senior Full-Stack Engineer – GenAI

• Design and extend production-grade LLM applications and agentic workflows using NestJS, XState v5, and the OpenAI SDK
• Build and maintain the conversation-machine substrate, including guard/action registries, flow validation with AJV, DB-driven flow configurations, and design-time tooling in Epicenter admin
• Build and evolve AI systems behind Epic Support Assistant, the player-facing support chatbot, and Agent Support Assistant, the AI copilot used by customer support agents
• Integrate with MCP servers for tool-use and agentic behaviors
• Evaluate, benchmark, and tune models across OpenAI, Gemini, Anthropic, and future providers; make model-selection decisions balancing quality, latency, throughput, reliability, and cost
• Troubleshoot production LLM issues including hallucinations, retrieval failures, prompt regressions, model drift, token inefficiencies, latency bottlenecks, and provider outages
• Build resilience mechanisms including retries, fallback routing, caching, streaming, rate limiting, and provider routing
• Instrument and tune model quality using Langfuse tracing, evaluations, prompt management, evaluation datasets, A/B testing, prompt versioning, and production telemetry
• Manage asynchronous workloads via BullMQ and caching with Redis
• Manage PostgreSQL persistence via Kysely

• Proven experience building and operating production LLM-powered systems similar in scope to chatbots, AI assistants, agent copilots, RAG systems, or LLM orchestration platforms
• Strong TypeScript/Node.js engineering; TypeScript strict-mode fluency
• Production AI experience: prompt engineering, RAG pipelines, agent design, tool calling, model evaluation, observability, and failure-mode analysis; shipped AI features, not just prototypes
• Full-stack experience across NestJS APIs, React UIs, databases, infrastructure, and production operations
• Ability to evaluate tradeoffs between model quality, latency, reliability, throughput, and cost
• Ability to troubleshoot AI systems across prompts, retrieval pipelines, model configuration, infrastructure, and application code
• State machine thinking; XState or similar experience is a strong signal
• Solid understanding of REST API design, async patterns such as queues and events, and caching strategies
• Strong testing culture covering unit, integration, and contract tests
• Experience working in a monorepo with multiple interconnected services
• Hands-on experience with MCP or building tool-use agentic workflows
• Familiarity with Langfuse or other LLM observability/evaluation platforms
• Experience operating AI workloads at scale
• Experience evaluating multiple foundation models and providers
• Experience building AI copilots, assistants, or conversational products
• Experience with semantic search and retrieval architectures
• Experience with AI gateways such as Portkey or similar platforms
• Experience with NestJS modules, providers, guards, interceptors, and dependency injection patterns
• Background in customer support or player support platforms
• Experience shipping under low-latency constraints, including chatbot response-time budgets and streaming
• Previous work in gaming or high-volume consumer products