About the Job: The GenAI Engineer position is a full-time opportunity based in Dubai, with hybrid working arrangements available. The role involves utilizing the company’s no-code builder to design and create AI agents and GenAI applications across various modules such as Application, Automation, Data, and AI Agent modules. Key responsibilities include engineering prompts and ensuring high-quality outputs in both Arabic and English, developing test sets for agent evaluation, and applying techniques for model training and fine-tuning. This role also requires conducting customer discovery sessions, defining user stories, and iterating on proofs of concept or minimum viable products collaboratively with stakeholders.
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Responsibilities:
- Solution Design & Build: Utilize the company’s no-code builder to create AI agents and GenAI applications using various modules including Application, Automation, Data, and AI Agent modules.
- Prompting & RAG: Engineer prompts, function calling, chunking/embedding, vectorization, reranking, grounding, and guardrails to ensure high-quality outputs in both Arabic and English.
- Agent Evaluation: Develop golden test sets and utilize agent-eval frameworks to monitor accuracy.
- LLM Model Training & Fine-tuning: Apply prompt engineering and other methods for training and fine-tuning models in Arabic and English.
- Customer Delivery: Conduct discovery sessions, define user stories and acceptance criteria, and build proof of concepts (PoCs) or minimum viable products (MVPs), iterating rapidly with stakeholders.
- Platform Expertise: Become a subject matter expert (SME) on the company’s platform and provide structured product feedback to influence the product roadmap.
Requirements:
- Experience: 2–4 years of experience in AI or LLMs, specifically in building real applications or agents.
- Languages: Professional proficiency in Arabic and English (read/write/communicate).
- In-depth Knowledge: Strong understanding of Gen AI concepts such as LLMs, teams of agents, MCP/A2A, RAG (including chunking, embeddings, reranking, vector databases), grounding/hallucination, AI governance, and evaluation.
- Model Operations Skills: Proficient in prompt engineering, creating golden test sets, using agent-eval frameworks, A/B testing, regression analysis, and basic fine-tuning methods (PEFT/LoRA).
- Integration Skills: Familiarity with REST/GraphQL APIs, OAuth, and webhooks; ability to stitch systems into cohesive end-to-end flows.
