AI Engineer - Autonomous Agents

About the role

vFairs, an event management platform, is looking for an experienced AI Engineer to build and scale AI-powered features within its virtual events platform. You will work at the intersection of the core product and the AI agent infrastructure, designing, building and shipping intelligent features that make events more engaging and easier to run for organizers and attendees. You will join a small, high-leverage AI team behind the agents and AI tooling that currently powers the MCP server and support experiences.

Key responsibilities

• Design and build fully autonomous AI agents that plan, sequence and execute multi-step event setup workflows with minimal human intervention.
• Architect multi-agent systems using LangGraph, including planner/executor patterns, task decomposition, sub-agent delegation and recovery logic.
• Extend and maintain the MCP (Model Context Protocol) server so agents can read and write event data, defining new tools, resources and permissions.
• Design guardrails, validation and human-in-the-loop checkpoints so agent actions on customer data stay safe, reversible and auditable.
• Build evaluation and observability pipelines tracking task success, drift, hallucinated actions and cost/latency, and use them to drive iteration.
• Own the full lifecycle of agentic features, from prototyping to production hardening and monitoring.
• Work with product to turn customer intent into reliable agent workflows, and with the core PHP/Laravel/Vue engineering team to integrate agentic services into the application.

Required profile

• 3+ years of AI experience.
• Hands-on production experience with LangGraph (or comparable agent orchestration frameworks) and FastAPI.
• Experience designing multi-step or multi-agent systems, not just single-turn chat or RAG.
• Strong Python skills and experience shipping LLM-powered applications (agents, RAG, tool calling, structured outputs).
• Judgment on when an agent should act independently versus wait for human confirmation.
• Comfort working across the stack, from API design to deployment, and strong cross-functional communication.

Required skills

• LangGraph and FastAPI
• MCP (Model Context Protocol) or similar tool/agent integration patterns
• Vector databases such as pgvector or Chroma and SQL-based retrieval
• LLM application architecture: prompt design, retrieval, evaluation and handling model failures
• Nice to have: PHP, Laravel and Vue.js; multi-cloud infrastructure; chatbot or support automation background; WebSocket streaming