Agentic AI Engineer
Remote ✓Main responsibilities • Design and build agentic AI systems, including autonomous agents, multi-agent orchestration, workflow state machines, and tool-using agents. • Develop LLM-driven agents capable of reasoning, planning, retrieval (RAG), and task execution across enterprise systems. • Build and maintain AI-powered automation workflows using platforms like n8n and Make to orchestrate business processes and cross-application integrations. • Integrate agents with APIs, CRM/ERP systems, collaboration tools, databases, and payment platforms using tool/function calling, MCP, and A2A patterns. • Implement robust execution logic (validation, retries, rate limits, fallbacks, error handling) to ensure reliability and scalability. • Design and manage RAG pipelines using embeddings, vector databases, chunking, and reranking strategies. • Establish safety guardrails, access controls, and human-in-the-loop workflows for high-risk actions. • Build evaluation, observability, and tracing pipelines to monitor performance, cost, latency, and reliability. • Monitor production systems, troubleshoot issues, and continuously improve agent performance and policies. • Prototype and benchmark emerging agentic AI frameworks and models. • Create technical documentation and communicate AI solutions effectively to cross-functional stakeholders. Requirements • Bachelor’s or Master’s degree in Computer Science, AI, Engineering, or related field. • 3+ years of software engineering experience (Python and/or TypeScript). • 1+ year building LLM-powered or agentic AI systems in production or near-production environments. • Experience with agent frameworks (e.g., LangChain, LangGraph, AutoGen, CrewAI, Semantic Kernel). • Hands-on experience with automation/orchestration tools (e.g., n8n, Make) in production settings. • Strong understanding of LLMs, embeddings, prompt engineering, structured outputs, and tool calling. • Experience designing REST APIs, microservices, and backend systems. • Familiarity with vector databases and RAG architectures. • Strong system design, debugging, and communication skills. Preferred : • Experience with MCP, A2A, or advanced agent communication patterns. • Advanced experience with n8n (custom nodes, self-hosting) or Make (complex scenarios). • Experience combining LLMs with workflow engines for document processing, reporting, chatbots, or decision support. • Familiarity with AI evaluation and observability tools (e.g., LangSmith, OpenAI Evals, Weights & Biases). • Experience with multi-agent systems, planning algorithms, RL, fine-tuning, or RLHF. • Knowledge of CI/CD pipelines and security best practices. • Experience in regulated industries (e.g., healthcare, finance, defense). • Relevant cloud or ML certifications. • Deploy and operate agent services in cloud environments (AWS, Azure, or GCP) using Docker, Kubernetes, Terraform, and CI/CD. • Experience with cloud platforms (AWS, Azure, or GCP), containerization (Docker, Kubernetes), and infrastructure-as-code tools.
Salary/Month
approx. €3,800-€6,400