Agent Builder

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. Agent Infrastructure & Backbones Scalable Deployments: Architect and maintain systems that support distributed AI agent execution at scale. Networking & Coordination: Implement robust protocols for data exchange and coordination across distributed agents. System Observability: Leverage monitoring tools (Prometheus, Grafana) to track agent performance and resource utilization. Resource Orchestration: Manage containerized environments (Kubernetes, Docker) and automate infrastructure (Terraform, Ansible) for seamless agent operations. Collaboration & Community Engagement Cross-Team Alignment: Work closely with product, research, and other engineering teams to identify key improvements and ensure agent features match real-world needs. DevRel & Content: Produce clear technical documentation, guides, and demos, driving open-source adoption and helping new users onboard quickly. Open-Source Contributions: Engage with the community by pushing code, merging pull requests, and resolving issues, championing decentralized AI best practices. 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. 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.

At Prime Intellect, we are on a mission to accelerate open and decentralized AI progress by enabling anyone to contribute compute, code or capital to train powerful, open models. Our ultimate goal? Openly accessible AGI that benefits everyone. But we can't do it alone and we want to do this together with you. We are building the infrastructure for decentralized AI development at scale. We aggregate global compute and enable researchers to collaboratively train state-of-the-art models through distributed training across clusters.