Agentic AI Engineer

As an AI Automation & Agents Engineer, the company expects you to perform the following tasks:

• Design and architect AI-driven autonomous workflows and multi-step agent systems using frameworks like LangGraph, LlamaIndex, or OpenAI Assistants.
• Build and secure Model Context Protocol (MCP) servers to safely expose internal capabilities, databases, and business-logic tools to AI agents.
• Integrate multi-LLM strategies (OpenAI, Anthropic, Gemini, Qwen), implementing dynamic routing, fallback mechanisms, and cost/latency optimizations.
• Scale operational automation by blending n8n/Make workflows with LLM logic, connecting backend services, vector stores, and RAG pipelines.
• Drive AI observability and governance, establishing guardrails, evaluation datasets, and monitoring dashboards to ensure predictable, secure, and compliant agent behavior.

You are the person they are looking for if you have...

• 7+ years of software engineering experience, with at least 2+ years designing and deploying LLM integrations, agentic frameworks, or AI automation in production.
• Production-grade proficiency in Python and/or TypeScript/Node.js, paired with a strong background in API design and cloud infrastructure.
• Expertise in the AI ecosystem, specifically with LangChain/LangGraph, OpenAI Assistants, vector databases (Pinecone, Qdrant, Redis), and advanced RAG retrieval.
• Hands-on mastery of automation tooling (n8n, Make) and the ability to build, version, and optimize structured prompts, schemas, and tool definitions.
• A security-first and observability mindset, capable of debugging agent behavior, tracking token spend, and setting up robust evaluation pipelines.
• A true builder’s mindset: High ownership, exceptional cross-functional communication, and the pragmatic ability to turn ambiguous business needs into scalable, autonomous systems.