Creatify
Software Engineer, Agent
San Francisco Bay AreafulltimemidAdded 3 days ago
About this role
OpenArt is seeking a Software Engineer to build the agent infrastructure powering its next-generation creative products. You'll develop agent harnesses, MCP servers, and frontend experiences that enable creators to direct AI-assisted video and creative workflows at scale.
What you'll do
- Build and extend the agent harness for tool use, context management, multi-step planning, and sub-agent orchestration
- Develop MCP servers and CLI tooling connecting agents to internal services, model vendors, and creative asset pipelines
- Author reusable Agent Skills and structured workflows for complex multi-step creative tasks
- Create evaluation frameworks and observability systems to monitor agent performance and catch regressions
- Ship production frontend experiences (React/Next.js) for agent-driven products end-to-end
- Partner with product, design, and GTM to translate user needs into technical solutions
What they're looking for
- Full-stack software engineering (2+ years production experience)
- LLM-powered agent development with real-world deployment
- Agent harness concepts (tool use, context management, planning, orchestration)
- Data modeling and schema design
- AI-assisted coding tools (Claude, Codex, Cursor)
- React/Next.js frontend development
- MCP server and CLI tooling development
- Product thinking and user experience design
Opens the application — the Jobs AI extension fills it for you. Set up autofill
Opens the official application on the employer’s site. No login required.
Creatify
Creatify builds an AI-powered video advertising platform that automates ad creation and distribution for major brands. The company is hiring Full-Stack Engineers, AI Research Engineers, Data Engineers, and Infrastructure/Platform Engineers to develop its SaaS product, data infrastructure, and cloud systems.
View all jobs at CreatifyLikely interview questions
- Walk us through a production LLM agent you've built—what were the hardest parts about tool use and multi-step planning at scale?
- How do you approach evaluating agent reliability before shipping to millions of users?