At AlDataset, we believe that data is only as valuable as the actions it powers. We are looking for a highly technical AI Agent Builder to join our team. Your mission will be to design, develop, and deploy sophisticated AI agents and automated workflows that leverage our datasets to solve complex business problems.
You aren't just a "no-code" enthusiast; you are a workflow architect who understands the underlying logic of APIs, data structures, and the nuances of different LLM architectures.
Key Responsibilities
- Architect Workflows: Design and implement end-to-end automation workflows using n8n to streamline data processing and agent tasks.
- API Integration: Connect disparate systems (CRMs, databases, social platforms, and proprietary AI tools) via RESTful APIs and Webhooks.
- Agent Development: Build autonomous and semi-autonomous AI agents capable of reasoning, tool-use, and multi-step execution.
- Data Pipeline Management: Assist in the ingestion and transformation of datasets from aldataset.com into RAG (Retrieval-Augmented Generation) systems.
- Optimization: Debug, monitor, and optimize existing workflows for speed, cost-efficiency, and reliability.
Technical Requirements
- n8n Mastery: Proven experience building complex, production-grade workflows in n8n (including self-hosted environments).
- API Expert: Deep understanding of RESTful APIs, JSON, OAuth2, and handling rate limits/pagination.
- AI Stack Knowledge: Experience with LLM orchestration frameworks (LangChain, LlamaIndex) and API implementations of OpenAI, Anthropic, or Groq.
- Coding Proficiency: Comfortable writing custom JavaScript or Python snippets within n8n nodes to handle complex data transformations.
- Database Skills: Familiarity with SQL (PostgreSQL) and Vector Databases (Pinecone, Weaviate, or Milvus).
The Ideal Candidate...
- Thinks in Systems: You see business problems as a series of inputs, transformations, and outputs.
- Is an "AI Native": You stay up to date with the weekly changes in the AI landscape and understand the difference between a prompt-engineer and an agent-builder.
- Is Detail-Oriented: You don’t just build "happy path" workflows; you build robust error handling and fallback logic.
Why Join AlDataset?
- Data-First Environment: Work at the source of the AI revolution—the data itself.
- Autonomy: We value builders who take ownership of their stack.
- Growth: You’ll be at the forefront of the "Agentic Workflow" shift in the industry.