AI Agent Builder _San Francisco-CA_Full-Time (FTE)_Direct Hire
Position: AI Agent Builder
Job Type: Full-Time (FTE)
Location: San Francisco-CA
Base Salary: $100,000 to $200,000 +Best-in-class benefits
Role Impact:
* This is a hybrid position spanning the quick and iterative development of AI agents and frameworks and advancing the underlying infrastructure. You’ll focus on:
* Building the next-generation AI agents to handle workload management and automation.
* Building out the underlying agent infrastructure that power different kinds of agents.
* DevRel + Content: Create technical content to drive adoption, engage communities for collaboration and feedback, and coordinate across teams to align technical and product goals.
Core Technical Responsibilities:
Rapid AI Agent Development:
* Prototype & Iterate: Build and refine AI agents for workload management, automation, and real-time decision-making.
* Framework Integration: Contribute to and extend agent frameworks to handle evolving feature requests and performance needs.
* Experimental Features: Quickly explore new agent capabilities (e.g., multi-agent collaboration, memory architectures) to guide design choices.
Technical Requirements:
Agent & Platform Skills:
* Python (FastAPI, Async): Proficiency in building agent logic, REST APIs, and backend services.
* Pytorch
* TypeScript/React/Next.js: Comfortable creating dashboards or other visualizations for agent monitoring.
* Real-time & WebSocket Systems: Experience building streaming or live-updating UIs to visualize agent activity.
* API Design: Ability to craft intuitive and efficient interfaces for agent communication.
Infrastructure Skills:
* Rust: Systems programming for high-performance agent components.
* Kubernetes, Docker: Container orchestration and production-ready deployments.
* Infrastructure automation and config management.
* Cloud Experience: Familiarity with scalable and cost-effective infrastructure.
Infrastructure Skills
* Rust: Systems programming for high-performance agent components.
* Kubernetes, Docker: Container orchestration and production-ready deployments.
* Infrastructure automation and config management.
* Cloud Experience: Familiarity with scalable and cost-effective infrastructure.
Nice to Have:
* GPU/ML Infrastructure: Understanding how to optimize agent training or inference on GPUs.
* Advanced AI/ML Knowledge: Familiarity with popular model architectures and training workflows.
* High-Performance Networking: Experience building low-latency data pipelines.
* Open-Source Contributions: Proven track record in community-driven projects.
Candidate Details:
*Seniority Level - Mid-Senior
*Minimum Education - Bachelor's Degree
