AI Enablement Specialist

Key Responsibilities

1. AI Research & Landscape Mapping

• Continuously monitor developments in AI relevant to engineering consultancy, project management, and AEC industries globally.
• Identify tools, frameworks, and approaches adopted by peer firms and assess their applicability to ECEC's context.
• Produce clear, jargon-free briefings and recommendations for senior leadership on AI opportunities.

2. Use Case Identification & Prioritization

• Work across ECEC's business units (Business Development, Operations, Project Management, HR, Finance) to understand workflows and identify where AI can create measurable value.
• Prioritize opportunities by impact, feasibility, and risk — distinguishing between quick wins and longer-term transformations.
• Map ECEC's current data assets and identify what data infrastructure is needed to support AI deployment.

3. Prototyping & Development

• Build working AI-powered tools and prototypes — including chatbots, document automation, data dashboards, proposal assistants, and workflow automation — using modern AI APIs, Python, and low/no-code platforms where appropriate.
• Work in an iterative, test-and-learn mode: ship fast, gather feedback, improve, or kill what doesn't work.
• Document all tools built, their logic, and how they are used — creating a growing internal knowledge base.

4. Risk, Security & Responsible AI

• Assess the data privacy, cybersecurity, and reputational risks of each AI application before deployment — particularly around client data, confidential project information, and regulatory compliance in Saudi Arabia.
• Establish and maintain an internal framework for responsible AI use at ECEC: what data can be shared with AI tools, what cannot, and under what conditions.
• Stay current on Saudi AI governance frameworks (SDAIA, PDPL) and ensure ECEC's AI activities are aligned.

5. Enablement & Change

• Train and coach colleagues on how to use AI tools effectively and safely — building internal capability over time, not dependency on a single person.
• Champion AI adoption across the company through workshops, demonstrations, and hands-on support.
• Act as the bridge between ECEC's technical needs and external AI vendors, consultants, or academic partners.

Qualifications & Requirement

sEducatio

• nBachelor's degree (minimum) in Computer Science, Artificial Intelligence, Data Science, Software Engineering, Information Systems, or a related Engineering discipline
• .Master's degree in AI or Data Science is an advantage but not required
• .Fresh graduates are welcome to apply — demonstrated self-learning and personal projects are valued over years of experience

.Technical Skills — Essentia

• lPractical experience working with AI tools and systems — through coursework, personal projects, hackathons, internships, or independent learning
• .Ability to write code (Python strongly preferred) to automate tasks, call AI APIs, or build lightweight tools
• .Familiarity with large language model (LLM) APIs such as OpenAI, Anthropic Claude, or Google Gemini and the ability to build simple applications on top of them
• .Comfortable using AI-powered productivity tools (e.g. ChatGPT, Copilot, Perplexity) and explaining how they work to non-technical colleagues

.Technical Skills — Advantageou

• sExposure to data analysis tools (Excel automation, SQL, Power BI, or similar)
• .Experience with automation or workflow tools (Zapier, Make, n8n, or Microsoft Power Automate)
• .Understanding of BIM, CAD software, or engineering project management platforms
• .Awareness of cloud platforms (Azure, AWS, or Google Cloud)

.Non-Technical Attributes — Critica

• lIntellectual curiosity and a drive to explore new technologies without waiting to be told what to do
• .Strong communication skills in both Arabic and English — the ability to explain AI concepts clearly to senior engineers, managers, and executives
• .A builder's mindset: comfortable with ambiguity, able to define their own objectives, and motivated by creating things that work
• .Sound judgment around risk: understanding that not every AI application is appropriate, and being transparent about what cannot or should not be done
• .Collaborative and humble — this role succeeds only through working closely with people across the business

.Domain Knowledge — Preferred but Not Require

• dFamiliarity with engineering, architecture, or construction project workflows
• .Understanding of project management concepts (scope, schedule, cost, quality)
• .Knowledge of Saudi regulatory frameworks related to data and AI (SDAIA, PDPL) is a plus

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