Agentic AI Product Engineer

Description

Job Summary: Aeolabs is seeking a Product Engineer with a builder mindset and technical capability to integrate AI agents into real-world value solutions, focusing on development, integration, and oversight of systems. Key Highlights: 1. Technical facilitator role in Agentic AI using Python/Node. 2. Development of AI logic using frameworks such as LangGraph/LangChain. 3. Rapid prototyping mindset to move from idea to MVP. At Aeolabs, we seek a Product Engineer with a builder mindset. We do not seek isolated specialists focused on a single technology, but rather professionals with technical ability and curiosity to integrate AI agents into solutions that generate real value. The Profile We are looking for a developer with a solid foundation in Python/Node who has transitioned into Agentic AI. Your role will be that of a technical facilitator: someone who can prototype an agent, connect it to a database, and ensure the end user can interact with it. Responsibilities * Agent Development: Implement AI logic (single- and multi\-agent) using frameworks such as LangGraph or LangChain. * System Integration: Build APIs and services that connect these agents with external tools and data sources. * RAG Implementation: Configure information retrieval workflows to optimize model responses. * Environment Management: Deploy and monitor solutions in the cloud, ensuring system stability and efficiency. * User Interface: Develop basic components in React to enable interaction with the AI tools built. Technical Requirements We understand technology evolves rapidly. We value learning ability, but for this role the following are required: * Professional experience with Python (FastAPI) or Node.js. * Familiarity with building AI agents and RAG workflows. * Experience working in containerized environments (Docker) and general knowledge of cloud services (Azure). * Ability to develop functional interfaces in React. * Use of NoSQL databases (e.g., MongoDB). Especially Valued * Experience in orchestration with Kubernetes (AKS). * Knowledge of vector databases and observability. * Rapid prototyping mindset: ability to swiftly move from idea to minimum viable product.