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Black & Grey HR

AI Technology & Data Lead

Al Khobar, SAفي الموقعدائمدوام كامل

تم النشر في 28 سبتمبر 2026

Black & Grey HR is recruiting for a well-established retail group in Saudi Arabia looking to hire a skilled AI Technology & Data Lead. The role will drive the technical vision, architecture, data foundation, and engineering standards across the organization’s AI portfolio, with hands-on involvement in solution design, integration, data architecture, and complex technical problem-solving.

Key Responsibilities

Technology & Solution Architecture

  • Define the technical roadmap and architecture for AI, data, and intelligent automation initiatives.
  • Translate business requirements into scalable technical architectures, integration solutions, and delivery plans.
  • Establish engineering standards and reusable architectures for APIs, data pipelines, cloud services, AI/ML solutions, security, testing, and deployment.
  • Review solution designs, code quality, infrastructure decisions, and production-readiness requirements.

Data & AI Enablement

  • Define data architecture covering ingestion, transformation, storage, data modelling, governance, quality, and access.
  • Enable enterprise data for AI/ML, GenAI, forecasting, recommendation, optimization, and automation use cases.
  • Guide integration of AI solutions with enterprise platforms including ERP, data platforms, e-commerce, CRM, loyalty, and operational systems.

Technical Delivery & Operations

  • Provide technical leadership across the complete AI lifecycle from discovery and design through deployment and ongoing operations.
  • Act as the senior technical escalation point for architecture, integration, cloud, data, performance, and production issues.
  • Work with technology vendors and implementation partners to review technical designs, estimates, dependencies, and delivery quality.
  • Drive requirements for monitoring, observability, documentation, technical handover, and production support.

Technical Leadership

  • Mentor engineers, data professionals, and delivery teams on AI, data, cloud, software engineering, architecture, and MLOps practices.
  • Collaborate with business, IT, security, enterprise architecture, and senior stakeholders to ensure effective technical decision-making.
  • Identify technical debt, architectural risks, and opportunities for standardisation and reuse across the AI portfolio.

Requirements

  • Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, AI, or a related technical discipline.
  • 8+ years of relevant technology experience, including 3+ years in technical leadership, architecture, or engineering leadership.
  • Strong hands-on experience across AI/ML engineering, data engineering, software architecture, APIs, cloud, and enterprise integration.
  • Proven experience designing and productionizing AI/ML or GenAI solutions in enterprise environments.
  • Strong proficiency in Python and SQL with the ability to review and contribute to technical solutions.
  • Strong understanding of data platforms, data modelling, ETL/ELT, data governance, and data quality.
  • Experience with cloud platforms; AWS is preferred.
  • Experience with Docker/Kubernetes, CI/CD, Infrastructure-as-Code, monitoring, DevOps/MLOps, and security practices.
  • Strong understanding of system design, APIs, microservices, event-driven architecture, and enterprise integration.
  • Proven experience working across multiple technical teams, vendors, and business stakeholders.
  • Experience in retail, grocery, e-commerce, supply chain, pricing, personalization, or customer analytics is an advantage.
  • Relevant AI, cloud, data, or architecture certifications are an advantage.

Benefits

- Competitive Salary + Benefits Package

ملخص الدور

نوع الوظيفة

دوام كامل

المهارات المطلوبة

Technical Solution Architecture & RoadmappingData Architecture (ingestion, transformation, storage, modelling, governance)AI/ML and GenAI solution design and productionizationTechnical Leadership & MentoringAPIs, Microservices and Enterprise IntegrationPython programmingSQLData Engineering (ETL/ELT, data platforms, data modelling)Cloud platforms (AWS)MLOps/DevOps (CI/CD, Infrastructure-as-Code, monitoring, deployment)Containerization & Orchestration (Docker, Kubernetes)Security, observability and production operationsStakeholder and vendor managementRetail/e‑commerce and customer analytics domain knowledge

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