AI Engineer

Aghanim is an integrated commerce, liveops automation, community engagement, and payments platform for video games.

Mobile games have traditionally depended on app stores for distribution, payments, and player relationships. We believe there is a better way. Aghanim helps game studios build direct relationships with players, sell directly, and build their future on their own terms. Today, more than 100 games worldwide are already building this future with Aghanim.

Our team brings together people across Los Angeles, New York, Seoul, Beijing, London, Lisbon, Belgrade and other locations around the globe, with deep expertise in gaming, fintech and technology. We move quickly, keep communication direct, and focus on getting things done. We believe the best people thrive when they have autonomy, ownership, and a stake in the company's success.

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

Key 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

Required Qualifications

• 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).

Preferred Qualifications

• 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