Principal Engineer, AI Systems

Role overview Set the technical direction for an AI platform that coordinates creative agents and delivers generated marketing work through real-time services. This is a hands-on principal-level role spanning architecture, reliability, and engineering leadership as a product moves from its initial build toward broader scale.

Responsibilities - Define the platform’s long-term architecture and align engineering, product, and leadership around its direction. - Own service boundaries, data models, event flows, multi-tenant design, and plans for scaling and failure handling. - Establish patterns for agent orchestration, tool use, model routing, guardrails, and output evaluation. - Make and document major platform decisions, including vendor choices and build-versus-buy trade-offs. - Set reliability, observability, latency, and cost targets for AI workflows, and guide the instrumentation needed to track them. - Stay hands-on with difficult engineering work while raising technical standards across the team.

Requirements - Principal-level engineering experience, with 10 or more years in the field. - A degree in computer science or a related discipline, or equivalent practical experience.

Nice to have - Experience with agent frameworks, MCP, or evaluation systems for language-model output. - Background in media-generation pipelines or GPU-backed and self-hosted inference. - Early-stage startup technical leadership, or public work in distributed systems or AI infrastructure.

Benefits and work setup Remote role in the U.S.; Pacific time zone preference. The description mentions flexible remote work, competitive compensation, and opportunities to grow with the team.