I am an AI Systems Engineer who transitioned from a background in distributed architectures and smart-contract optimization into building production-grade generative AI systems. What makes me unique is my focus on the systems and economic side of AI; I specialize in context engineering, rolling summaries, and designing dual-layer Context Graphs that couple corporate knowledge with active agent decision traces. Recently, I engineered prompt-caching strategies that pushed cache hit rates above 90%, significantly slashing inference latencies and API overhead. I have deep experience building stateful multi-agent assistants, LangGraph orchestrations, and custom Model Context Protocol (MCP) servers directly alongside startup founders. I am looking for a core AI Engineering role at a high-velocity, venture-backed startup where I can own the development of autonomous agent networks, complex tool-calling validation pipelines, and real-time streaming architectures.
No skills.