AI Development Expert — Automation & Product Shipping
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Key skills for this role
About the Role
We're looking for a senior AI engineer who ships. Not someone who demos and disappears — someone who takes a process, figures out where AI creates leverage, and has a working product in production within days, not months.
Key Skills for This Role
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Overview
We're looking for a senior AI engineer who ships.
Not someone who demos and disappears — someone who takes a process, figures out where AI creates leverage, and has a working product in production within days, not months.
You're equally comfortable writing Python and spinning up a no-code workflow in Make or n8n.
You've shipped multiple AI products that real people use.
What You'Ll Do
- Identify high-impact automation opportunities across company operations and move fast to ship solutions
- Build and deploy AI-powered products end-to-end — from prompt design to production pipeline
- Use whatever gets the job done fastest: custom code, LLM APIs, no-code tools, or a combination
- Integrate AI into existing workflows, tools, and systems (CRM, databases, internal tools, APIs)
- Set up monitoring and feedback loops so shipped products actually keep working
- Stay current with the AI tooling landscape — new models, new frameworks, new approaches — and use them
Requirements
- 7+ years of software engineering experience, with at least 4 years building AI/ML systems
- Proven track record of shipping multiple AI products to production — not prototypes, real products
- Strong Python skills and hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini)
- Comfortable with no-code and low-code automation tools (Make, Zapier, n8n, Airtable, etc.)
- Experience with RAG architectures, agents, and LLM orchestration frameworks
- Fast-paced environment survivor — you've worked in startups or high-velocity teams where speed matters and you thrived
- You think in AI-first: your default when seeing a manual process is "how do I automate this with AI?"
- Nice to have
- Experience with multi-agent systems and agentic workflows
- Background in ML Ops — experiment tracking, model versioning, deployment
- Exposure to voice AI, computer vision, or document processing pipelines
- Built internal tools that replaced manual work entirely
- Must be loctated in UAE (No relocation / remote possibility)
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