AI Data Engineer

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October 8

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Spiral Scout

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Artificial Intelligence • SaaS • Enterprise

Spiral Scout is a technology partner that specializes in AI-powered software development and digital transformation. They build agile teams to deliver industry-leading AI solutions for startups and enterprises, focusing on AI-driven software innovation, agile development, and on-demand tech expertise. With a history of successful projects, Spiral Scout helps businesses improve efficiency, optimize legacy systems, and streamline operations through custom AI frameworks such as Wippy. ai. Their services extend to enhancing eCommerce platforms, educational tech development, and integrating payment systems. Serving over 300 companies, Spiral Scout positions itself as a reliable partner for mid-sized companies and startups looking to scale their technology capabilities, modernize their systems, or require premium tech talent quickly.

51 - 200 employees

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

📋 Description

• Build and maintain data pipelines (Python, SQL, ETL, APIs) to prepare structured and unstructured data for AI workflows. • Translate client problems into orchestrated AI workflows, balancing automation and human-in-the-loop design. • Configure multi-agent logic (planner/worker, feedback loops) using LangChain, Wippy, n8n, Zapier, Make, or custom Python code. • Prototype and ship proof-of-concepts: onboarding bots, quoting assistants, presales flows, project management helpers. • Facilitate scoping workshops with stakeholders to clarify requirements and design workflows. • Collaborate with engineers and product leads to create reusable AI workflow templates and automation patterns.

🎯 Requirements

• Strong data engineering experience: Python + SQL, pipelines, ETL, API integrations. • Experience working with data ahead of AI: cleaning, structuring, connecting multiple sources. • Hands-on with AI tools: ChatGPT, Claude, LangChain, n8n, Zapier, Make, Autogen, or similar. • Understanding of LLM orchestration beyond prompt engineering. • Systems thinking: ability to design workflows with multiple agents, branching logic, loops, and state. • Strong communication skills: able to explain AI/data concepts and lead workshops with technical and non-technical stakeholders. • Experience with agent-based frameworks (LangGraph, CrewAI, AutoGen). • Designed human-in-the-loop workflows (customer support, onboarding, quoting, project management). • Prototyping with low-code/no-code platforms (Zapier, Airtable, Streamlit, custom GPTs). • Familiarity with cloud platforms (AWS, GCP, Azure). • Exposure to ML practices (fine-tuning, RAG, evaluation, multimodal inputs).

🏖️ Benefits

• Start with a paid pilot project to evaluate collaboration. • Work at the cutting edge of AI workflows and data-driven automation. • Fully remote, flexible schedule. • Fast-moving, innovation-driven culture where ideas quickly turn into practice. • Pathway to extended part-time or full-time engagement.