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AI Engineer(RAG, LLM, Generative AI)
Ekaa Technology Solutions and Services
Abu Dhabi, UAE
Full-time
Entry
Onsite
Discovered Today
LLM application engineeringGenerative AI developmentRAG architectureSemantic search and embeddingsVector databasesPrompt engineering
Free
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LLM application engineeringGenerative AI developmentRAG architecture
Role Overview
Independently take an AI use case from problem definition through architecture, prototype, evaluation, production implementation, monitoring, and continuous improvement.
Deliver solutions that are reliable, secure, explainable, and scalable.
Key Skills for This Role
LLM application engineeringGenerative AI developmentRAG architectureSemantic search and embeddingsVector databasesPrompt engineering
Full Job Posting
Required Technical Skills
- Strong experience in LLM application engineering and Generative AI development.
- Hands-on expertise in RAG architecture, semantic search, embeddings, chunking, retrieval strategies, and vector databases.
- Strong knowledge of prompt engineering and prompt architecture.
- Experience designing and implementing AI agents and agentic workflows.
- Experience with LLM evaluation, grounding, guardrails, and hallucination mitigation.
- Experience with multi-model and multi-stage LLM pipeline design.
- Strong Python programming skills and experience developing production-grade APIs and services.
- Experience integrating LLMs with enterprise applications, APIs, databases, and knowledge repositories.
- Practical experience with AI-assisted development tools such as Claude Code, Cursor, and Codex.
- Familiarity with LLM providers, model selection, inference patterns, token and context management, and cost-performance optimization.
- Knowledge of AI application observability, evaluation metrics, and production monitoring.
Preferred Skills
- Experience with forecasting, predictive analytics, risk analysis, or anomaly or conflict detection.
- Experience implementing enterprise AI governance and responsible AI practices.
- Knowledge of AI security, prompt injection defense, data protection, and access-control mechanisms.
- Experience with cloud platforms and containerized or cloud-native application architectures.
- Familiarity with CI/CD, DevOps, and MLOps practices.
- Experience building AI solutions with auditable outputs and source-level traceability.
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