AI Agent Engineer

Our client, an innovative Enterprise AI Platforms company based in Munich, is looking for an AI Agent Engineer to design and build intelligent AI agents that securely interact with business data, enterprise applications, and operational systems. About the Role You'll work at the forefront of agentic AI, developing autonomous workflows that integrate with internal knowledge bases, APIs, databases, and business tools while ensuring enterprise-grade security, reliability, and governance. Responsibilities Designing and developing enterprise AI agents capable of executing complex business workflowsBuilding secure integrations with enterprise systems, APIs, internal knowledge bases, and operational tools using MCPDeveloping multi-agent orchestration and reasoning workflows with LangGraphBuilding scalable backend services and APIs using FastAPI and PythonDesigning Retrieval-Augmented Generation (RAG) solutions using modern vector databasesImplementing robust security, authentication, permissions, and governance controls for enterprise AI applicationsOptimising agent performance, response quality, reliability, and operational efficiencyCollaborating with Product Managers, AI Engineers, and Software Engineers to deliver production-ready AI capabilitiesMonitoring, testing, and continuously improving agent behaviour in live environmentsHelping define the architecture of the company's next-generation Enterprise AI platform Qualifications 4+ years of experience in Python Software Engineering, AI Engineering, or Backend Development Required Skills Strong commercial Python development experienceHands-on experience building applications with Large Language Models and AI APIsExperience developing AI workflows using LangGraph or similar orchestration frameworksExperience integrating enterprise applications through APIs and modern backend architecturesStrong knowledge of FastAPI and modern Python application developmentExperience implementing RAG architectures using vector databases such as Pinecone, Weaviate, or QdrantPassion for building secure, scalable, and production-ready AI applications Preferred Skills Experience implementing the Model Context Protocol (MCP) or similar enterprise integration frameworksExperience deploying AI services on Kubernetes or cloud-native infrastructureKnowledge of agent evaluation, observability, and AI monitoring techniquesExperience with cloud platforms such as AWS or AzureFamiliarity with CI/CD pipelines and Infrastructure as Code using TerraformExperience working in Enterprise AI, AI SaaS, Developer Tools, or Automation Platforms