Senior/Staff Software Engineer, Agent

🎨 About OpenArt

OpenArt is an AI storytelling and visual creation platform used by millions of creators worldwide. We're building the next generation of creative tools powered by cutting-edge AI — enabling anyone to create videos, visuals, characters, and stories with unprecedented speed and imagination.

We believe the future of creativity is AI-native, and we're shaping that future.

🚀 Why Join OpenArt

Ground floor of a new category — help define what "agent" means for creative work, the way Director redefined what "directing" means for video. You'll set the architecture everything else is built on.

Own the whole agent layer — not a service, not a slice. Harness, orchestration, memory, evals, tooling: the entire system is yours to design and lead.

Real scale, real stakes — your agents run for millions of creators, and every improvement in reliability, latency, or quality shows up in the product within days.

Founder-led engineering culture — both founders are technical and deeply involved in product and architecture.

AI-native product — you'll decide how frontier models get orchestrated, constrained, and exposed as experiences that feel effortless rather than technical.

High ownership, low process — we value judgment, clarity, and speed over bureaucracy.

🎯 About the Role

We're hiring a senior or staff engineer to lead the agentic architecture behind OpenArt's next generation of creative products, starting with Director — which lets anyone "vibe direct" a multi-minute cinematic video by chatting with AI. You'll own the agent infrastructure that pushes experiences like this further: longer-horizon planning, tool use across multiple model vendors, memory across sessions, sub-agent orchestration, and the harness that keeps all of it reliable in production.

This isn't a research role — it's a product-and-systems leadership role. You'll define the architecture of the agent harness (tool use, context engineering, multi-step planning, orchestration, evaluation), set the engineering standards the team builds against, and stay hands-on: building the MCP servers and CLI tooling around it, and shipping the frontend experiences on top of it. You'll work directly with the founders and design to turn "what should this agent be able to do" into a system that actually does it — reliably, at scale — and you'll be the technical voice that decides how.

🛠 What You’ll Do

Own the end-to-end architecture of the agent harness that powers OpenArt's conversational and autonomous creative workflows: tool use, context/memory management, multi-step planning, and sub-agent orchestration

Design how agents plan and execute long-running creative tasks — scene planning, storyboarding, asset generation, revision loops — across multiple model vendors, with clear failure modes and recovery paths

Build and maintain MCP servers and CLI-based agent tooling that connect our agents to internal services, external model vendors, and creative asset pipelines

Author reusable Agent Skills and structured workflows, and define the patterns other engineers use to add new ones

Build the evaluation and observability stack — automated evals, regression suites, tracing, and quality gates — so the team knows when an agent is working well and catches regressions before users do

Drive reliability, latency, and cost per successful run as first-class metrics, not afterthoughts

Ship polished, production frontend experiences (React/Next.js) for agent-driven products, end to end

Set the technical bar for agent engineering at OpenArt: architecture reviews, engineering standards, and mentorship as the team grows around you

Track the fast-moving agent ecosystem (MCP, Agent Skills, orchestration frameworks, new model capabilities) and decide what belongs in OpenArt's stack — and what doesn't

Partner closely with founders, product, design, and GTM to translate user needs into technical direction, and communicate trade-offs clearly

⚙ What We’re Looking For

Core Requirements

7+ years of full-stack engineering experience shipping and owning production systems at scale, including 2+ years building LLM-powered agents in production — not just prototypes or demos