Senior Agentic AI Engineer

Want to help us help others? We’re hiring! GoFundMe is the world’s most powerful community for good, dedicated to helping people help each other. By uniting individuals and nonprofits in one place, GoFundMe makes it easy and safe for people to ask for help and support causes—for themselves and each other. Together, our community has raised more than $40 billion since 2010. Join us! We’re seeking a Senior Agentic AI Engineer to build production-grade autonomous agents and orchestration systems that reshape the future of fundraising, campaign optimization, and donor engagement. We’re looking for a senior technical member who can build LLM-based autonomous agents and multi agent orchestration systems with advanced reasoning, multi-step planning, and real-time orchestration capabilities. You’ll design, deploy, and scale intelligent AI agents that reason, plan, and act in dynamic fundraising ecosystems. You’ll enable multi-agent collaboration, long-term memory, and cross-agent communication in production environments serving millions of users. This is a hybrid position. Candidates considered for this role will be located in Buenos Aires, Argentina. The Job Agent Architecture & Planning Design and implement LLM-based autonomous agents that perform beyond simple responses — including planning, reasoning, tool-use, and long-term task decomposition. Engineer context- and memory-rich agents that integrate structured data, external APIs, and conversational context to optimize outcomes. Multi-Agent Orchestration Build production-scale orchestration frameworks using tools such as LangGraph, Pydantic AI, Google ADK, and CrewAI to orchestrate complex workflows across campaign creation, optimization, and tracking in distributed microservices architectures. Implement agent-to-agent (A2A) communication protocols using Model Context Protocol (MCP), enabling tool discovery and dynamic peer -to-peer task delegation between specialized agents in our fundraising ecosystem. Infrastructure & Deployment Develop microservice-based, cloud-native infrastructure for autonomous agent deployment with Docker/Kubernetes, observability tooling, and cloud platforms (AWS/GCP). Ensure enterprise-grade performance, monitoring, and fault tolerance in agent systems supporting large-scale fundraising workflows. Design sophisticated prompt strategies, agent memory architectures, vector and graph database implementations for maintaining context across multi-turn conversations and long-running campaign lifecycles Agent Memory & Tooling Systems Architect and optimize vector and graph database integrations (e.g., Pinecone, Weaviate, ChromaDB) for agent memory and semantic recall. Build custom agentic frameworks for use cases across campaign storytelling, optimization, and donor engagement. Architect frameworks from scratch tailored to fundraising domain challenges, incorporating advanced tool-use capabilities that integrate with platform APIs, knowledge graphs, and external systems. Evaluation & Governance Build and scale LLM evaluation pipelines, including human-in-the-loop and automated frameworks. Embed safety, fairness, transparency, and explainability into agent behavior. Implement real-time guardrails and auditing mechanisms. You 6+ years in software engineering, with 3+ years hands-on building production-grade AI/ML systems. Deep expertise in LLM agent frameworks (LangGraph, Google ADK, CrewAI, AutoGen, Pydantic AI, LangChain). Proven ability to architect agentic systems from scratch, including planning/reasoning flows and multi-agent orchestration. Strong Python/TypeScript skills and experience in microservices and distributed infrastructure. Familiarity with vector databases (e.g., Pinecone, ChromaDB), knowledge graphs (Neo4j, Graphiti), and RAG pipelines. Deep autonomous agent architecture knowledge including advanced reasoning, planning, task decomposition, multi-step automation, tool-use patterns, evaluation systems beyond simple response generation Enterprise integration expertise with RESTful APIs, A2A interoperability, webhook systems, Model Context Protocol (MCP) tools for dynamic tool discovery Production experience with cloud-native infrastructure (Docker, Kubernetes, AWS/GCP). Demonstrated experience with reinforcement learning, agent optimization, and agent evaluation techniques. Strong understanding of agent safety, bias mitigation, transparency, and ethical design practices. Preferred Experience in fundraising, fintech, or high-compliance domains involving sensitive data Familiarity with agentic evaluation strategies and AI observability tooling Contributions to open-source agent frameworks or AI developer communities Experience integrating agent frameworks into real-world applications with measurable outcomes Why you’ll love it here Make an Impact : Be part of a mission-driven organization making a positive difference in millions of lives every year. Innovative Environment : Work with a diverse, passionate, and talented team in a