Senior AI Systems Architect

We are seeking a Senior AI Systems Architect to design, build, and scale a self-optimizing multi-agent framework. You will lead the development of a deterministic, autonomous infrastructure that moves beyond standard routing. This role focuses on combining state machine orchestration, reasoning distillation, and continuous architectural evolution to create a highly secure, self-improving AI ecosystem.

Responsibilities:

Core Architecture: Design and deploy highly deterministic, directed-graph orchestration layers to manage data flow and execution state across distributed AI nodes.

Self-Improving Loops: Integrate evolutionary algorithms and learn-experiment-analyze cycles, allowing the system to autonomously optimize its own routing and node logic.

Reasoning Distillation: Build mechanisms that capture probabilistic LLM reasoning trails and convert them into static, repeatable skillsets to reduce latency and hallucination.

Systems Governance: Develop an overarching control plane to enforce cross-agent policies, secure OS-level sandboxing, and strict API execution limits.

Prerequisites & Technical Requirements:

Advanced Orchestration: 5+ years of experience building complex state machines, DAG-based execution engines, and multi-agent workflows (e.g., LangGraph or similar).

AI-for-AI Experience: Deep understanding of automated research loops and evolutionary AI systems that can hypothesize, test, and analyze their own logic.

Execution Environments: Proven track record of managing secure agent deployments using meta-harnessing principles, declarative policies, and isolated cloud environments.

Systems Engineering: Strong proficiency in Python/TypeScript, asynchronous stream processing, and state checkpointing (e.g., PostgreSQL).

Security & Telemetry: Experience implementing robust AI security layers, intent-based controls, and unified telemetry for enterprise-scale deployments.