Summary
✨ AI‑Generated
Seeking top-tier generative AI specialist to create robust AI-driven workflows integrating with legacy services, leveraging n8n platform for seamless integration and scalable solutions.
Highlights
Expert GenAI engineer needed with 8+ years experience to build production AI applications using n8n for a Saudi organization.
Description
Position Summary
We are seeking an expert GenAI engineer with 8+ years of relevant software, data or AI engineering experience to build and operate production AI applications for a Saudi organization, using n8n to connect AI features to existing services.
The work must be reliable, testable and well documented.
Only client-approved models, tools and hosting may be used, and client data must never go to public AI services or be used for training outside approved scope.
Responsibilities
Build and customize LLM applications aligned with approved use cases and architecture.Implement production n8n workflows connecting AI to authenticated APIs, enterprise services and approved data.Design for retries, timeouts, duplicate events, failed steps and controlled manual recovery.Write supporting code, integrations and data transformations where n8n alone falls short.Set up prompt/config versioning, repeatable evaluation, output validation and logging; investigate issues with QA and DevOps.Review the mid-level engineer's work and deliver source, documentation, operating guidance and knowledge transfer.
Requirements
Essential
8+ years in software, data or AI engineering, including recent production GenAI work.Current, separately demonstrable capability in both GenAI and n8n (8 years in each tool is not required).Relevant bachelor's degree (CS, AI, data science, software engineering) or equivalent.Proven production LLM/GenAI delivery, beyond experiments or prompt demos.Hands-on n8n: webhooks/APIs, authentication, secrets, error/retry branches, deployment and support.Strong Python (or comparable) skills and ability to review integration code.Able to evaluate outputs against business needs, control data access and explain reliability/security trade-offs.Compliance with client-approved models, tools and hosting.Preferred
RAG or document-data integrationArabic-language applications, government/regulated services, AI quality testingCI/CD for AI/workflow assets, containerization, model/provider portability
