AI Manager - Agentic AI
We’re building production-grade AI agents in Python that automate real workflows across Finance and our wider Operations. We are searching for an AI Manager (80% hands on).
This role reports to the AI Director in our DAMAC Executive Heights Head office in Dubai. You’ll design, build, and operate agentic platforms and LLM-powered applications end-to-end including architecture, integration, evaluation, monitoring, and continuous improvement. Success is measured in autonomous resolution, workflow automation, and measurable time/cost savings, not proof of concept. You’ll need evidence of what you’ve shipped, how many current users and what tangible benefits you’ve made with your product.
Evidenced Skills:
- Production LLM/agent systems that reduce manual admin and speed up finance and operations workflows
- Integrations across CRM, ERP, MI tools and Cloud services
- Operating AI systems properly: reliability, observability, SLAs, and performance
- Enterprise-grade security: permissions, PII handling, audit logging, and guardrails against prompt injection / data exfiltration / unsafe actions
- Shipped LLM-powered systems to production with uptime, monitoring, and business KPIs
- Strong hands-on engineering + applied DS/ML capability
- Comfortable building in-house (no vendor-led delivery), owning outcomes, and working across business functions
- Line managed others as we grow and scale our team
- Bachelor’s Degree (Minimum) In Computer Science, Computer Engineering, Data Science, Statistical Modelling
- A history of Python coding experience, 5 yrs + as an Engineer, Developer or Data Scientist, moving in to Technical Leader / Hands on Management.
Tech stack: Python, Multi Agentic AI product build, Orchestration Layers, APIs to Data lakes. Knowledge and Data Layers, Azure.
If you’ve built real agentic systems that run in production and drive measurable operational impact, please apply.
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- Posted
- Jan 16, 2026
- Type
- Full-time
- Level
- Mid-Senior
- Location
- Dubai
- Company
- DAMAC Group
Industries
Categories
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