Agentic AI Engineer

Main responsibilities

• Design and develop agentic AI systems including autonomous agents, tool-using agents, multi-agent orchestration, and workflow state machines 
• Design, build, and maintain AI-powered automation workflows 
• Build LLM-driven agents capable of reasoning, planning, retrieving knowledge, and executing tasks across enterprise systems 
• Integrate agents with internal APIs, CRM/ERP platforms, Jira, Confluence, Slack, email, databases, payment systems, and other business tools using function/tool calling, MCP (Model Context Protocol), and A2A patterns 
• Develop end-to-end AI automations that combine LLM capabilities solving repetitive tasks such as document processing, lead enrichment, customer support triage, reporting, and data synchronisation across systems 
• Connect AI agents to automation platforms via webhooks, API triggers, and custom nodes; manage scheduling, error handling, and conditional branching within automation workflows 
• Implement tool-calling schemas, input validation, error handling, retries, rate limits, and fallback logic to ensure reliable agent execution 
• Design and maintain RAG pipelines using vector databases, embedding models, reranking, and chunking strategies to ground agent outputs in enterprise knowledge 
• Build safety guardrails including content filters, policy constraints, tool access controls, and human-in-the-loop approval flows for high-ris