Full-Stack Engineer, Agent Management Platform
Remote • San Francisco, California, United States • Full-time
Posted 3mo ago
About the job
CrewAI is seeking a Full-Stack Engineer to build and enhance their Agent Management Platform. This web product is central to how teams create, deploy, monitor, govern, and manage agentic automations in production. This role has a strong frontend bias and involves working across a modern tech stack including Rails, React, TypeScript, and Hotwire to make complex AI infrastructure accessible and user-friendly.
Responsibilities
- Build user-facing platform experiences across various surfaces including Studio, deployments, observability, and admin.
- Ship polished frontend work using React, TypeScript, Vite, Tailwind, Hotwire, Stimulus, and Rails views.
- Own full-stack features from database models and service objects to controllers, jobs, APIs, and UI.
- Design workflows for complex agent management concepts such as organizations, permissions, authentication, LLM connections, and deployment status.
- Integrate with external systems including authentication providers, GitHub, Slack, and Stripe.
- Write high-quality tests across both Rails and frontend code.
- Partner with runtime and open-source engineers to improve the visibility and usability of CrewAI's execution model within the platform.
Requirements
- 7+ years of full-stack product engineering experience, preferably in B2B platforms with complex workflows.
- Excellent frontend judgment with expertise in React, TypeScript, component design, state management, and data-heavy screens.
- Solid backend ability with Ruby/Rails or a comparable MVC/web framework, including data modeling, service code, job debugging, and API design.
- Comfort working with PostgreSQL, background jobs, caching, external APIs, and production-facing product behavior.
- Ability to create clear UX for technically complex systems, making concepts like deployment state and errors understandable.
- Strong testing habits and comfort shipping in a fast-moving codebase.
- Sufficient AI/LLM curiosity to understand agentic concepts and product needs.