Python Developer (AI)

Description

Summary: Seeking a solution-oriented AI Engineer to design and build production-grade multi-agent LLM systems, focusing on understanding user outcomes and engineering reliable solutions. Highlights: 1. Design and implement multi-agent LLM systems with high orchestration complexity 2. Focus on systems engineering/architecture for reliable AI, not just ML 3. Opportunity to build agent infrastructure, multimodal pipelines & custom tools We are looking for a **solution\-oriented AI Engineer** who can design and build production\-grade **multi\-agent LLM systems**. The key expectation is not just writing code, but **understanding the desired user outcome and engineering systems that reliably deliver it**. This role is closer to **systems engineering / architecture** than classical ML. You will work independently, explore our APIs and product flows, and build agent\-based solutions that integrate deeply with the platform. **Context** ----------- * Product platform with multiple internal APIs * Agents interact with platform APIs and product workflows * High variability of use cases and flows * Relatively small data volumes per agent, but **high orchestration complexity** * Agents must operate autonomously with **tools, routing, memory and fallback strategies** * Backend stack mainly **Python**, frontend **TypeScript** **Responsibilities** -------------------- * Design and implement **multi\-agent systems** (orchestrator \+ worker agents) * Build agent infrastructure: + routing + memory + tool execution + fallback strategies * Develop **multimodal pipelines** (text images) * Integrate and abstract different model providers * Build **custom tools and MCP servers** * Connect agents to internal platform APIs * Read and analyze platform API specs and source code (Python backend / TypeScript frontend) * Extend or build **API layers / adapters** when necessary * Implement automated testing and **LLM evaluation pipelines** * Debug agent behavior and improve reliability **Requirements** ---------------- * Familiarity with the **gamedev domain**, including experience in **analytics**, **payments**, or similar areas of the industry * Strong **Python backend development** (async, APIs, services) * **Commercial experience building multi\-agent LLM systems** * Experience with agent frameworks like: + LangChain + LangGraph + AutoGen + CrewAI + LlamaIndex + Pydantic AI * Experience designing: + agent orchestration + tool calling + routing + memory systems * Experience building **multimodal pipelines** (text \+ image generation) * Experience integrating multiple model providers: + OpenAI + Anthropic + local / self\-hosted models * Vector databases: **Qdrant / Pinecone / Weaviate** * Redis or similar caching / state layers * Experience with **production\-grade development practices** + testing + debugging + observability ### **Important: commercial experience is required (not pet projects).** **Nice to have** ---------------- * ML background or practical ML knowledge * Experience designing **AI product architectures** * Experience building **agent evaluation / benchmarking frameworks** * Experience working with **large API ecosystems** * Experience with AI observability tools **Working Style** ----------------- * Strong **ownership and autonomy** * Ability to work from **problem architecture implementation** * Comfortable exploring unfamiliar codebases, APIs and product logic * Focus on **engineering reliable AI systems**, not just experimenting with models