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Urgent! Artificial Intelligence Engineer Job Opening In Abu Dhabi Emirate – Now Hiring Calidus, LLC

Artificial Intelligence Engineer



Job description

About the Role

The Applied AI Engineer will design, develop, build and deploy on-premise AI solutions, integrating large language models (LLMs), retrieval-augmented generation (RAG), and intelligent agents into enterprise systems.

This role combines machine learning engineering, generative AI development, and prompt design to deliver secure, scalable, and business-aligned AI applications.

Key Responsibilities

  • Fine-tune and optimize open-source LLMs using techniques such as LoRA/QLoRA.

  • Quantize and deploy models efficiently using frameworks like vLLM, Triton, or TensorRT.

  • Evaluate model performance with domain-specific benchmarks and metrics.

  • RAG & AI Development: Implement embeddings, vector databases, and retrieval-augmented generation pipelines.

  • Develop AI agents and workflows using frameworks such as LangChain, LangGraph, or Semantic Kernel.

  • Connect AI systems securely with enterprise platforms (ERP, CRM, IoT, PLM, file systems).

  • Prompt & Workflow Design: Engineer prompts, structured templates, and chaining logic to improve reliability.

  • Collaborate with business teams to tailor AI outputs to specific use cases and compliance requirements.

  • Implement guardrails, grounding, and refusal rules to reduce hallucinations and ensure safe outputs.

  • Collaboration & Delivery: Work with Data Engineers and MLOps teams to integrate clean data pipelines.

    Partner with domain SMEs to align AI solutions with business processes.

    Document workflows, best practices, and provide internal training on AI usage.

Required Skills

  • Strong proficiency in Python and ML/AI libraries (PyTorch, HuggingFace, Transformers).

  • Experience with LLM fine-tuning, optimization, and inference serving (LoRA, vLLM, Triton).

  • Hands-on expertise with vector databases (Qdrant, Milvus, pgvector) and RAG pipelines.

  • Knowledge of agent frameworks (LangChain, LangGraph, Semantic Kernel) and tool integration.

  • Practical experience in prompt engineering and structured output design.

  • Familiarity with on-prem AI deployment, containerization (Docker/Kubernetes), and API integrations.

  • Strong problem-solving mindset and ability to translate business needs into AI solutions.


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