AI Platform Engineer, Agent Systems

Що робити

What You Will Own
Skills runtime. Design the format, packaging, loading, and execution layer for the structured domain knowledge that turns a generic model into a music-production specialist. This is our most distinctive platform primitive and it is largely greenfield.
Context, memory, and state. Build the systems that keep agents performant and coherent across long, multi-step creative workflows. This includes context compaction, short-term working memory, durable cross-session memory, session stat

Five or more years shipping production platform or infrastructure software that other engineers have built on top of.
Demonstrated experience designing tool interfaces for LLM consumption. You can explain what makes a tool schema discoverable and usable by a model versus merely technically correct.
Demonstrated experience building context, memory, or state-management systems beyond framework defaults, including compaction, durable memory, or session persistence. You have diagnosed agent failures from raw execution traces and made targeted harness changes in response.
Strong proficiency in TypeScript and Python.
Experience with the Model Context Protocol (MCP) or similar tool-connectivity standards.

Background in music production, audio engineering, or another creative-tool domain, including as a serious hobbyist.
Experience with real-time audio systems, professional audio software, or other latency-sensitive environments.
Experience making a complex desktop or professional application agent-accessible, in any domain with a rich object model (DAW, IDE, design tool, CAD).
Experience building middleware or hook architectures that allow others to customize agent behavior without modifying core code.

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