Senior Agentic AI Engineer - Abu Dhabi
2 days ago
Job description
Role Summary:
We are looking for a Senior LLM Engineer with deep expertise in Large Language Model development, orchestration, and application engineering.
The ideal candidate has 3–5 years of hands-on experience building and deploying AI systems using LangChain, LangGraph, and related frameworks.
You will be responsible for designing, implementing, and optimizing complex, multi-agent LLM applications that drive real business value.Key Responsibilities:
Design, build, and optimize LLM-based systems leveraging LangChain, LangGraph, and vector databases.
Develop and maintain modular prompt pipelines, agents, and tools that enable dynamic reasoning and contextual understanding.
Integrate LLMs with APIs, databases, and internal tools for seamless automation and data interaction.
Fine-tune, evaluate, and deploy foundation models (e.g., OpenAI, Anthropic, Mistral, Llama) for domain-specific applications.
Implement retrieval-augmented generation (RAG) and knowledge graph reasoning pipelines.
Collaborate with cross-functional teams — product managers, data engineers, and researchers — to bring LLM-driven products to life.
Contribute to LLM system architecture design, ensuring scalability, maintainability, and performance.
Stay current with emerging AI frameworks, model APIs, and orchestration patterns.
Key requirements:
Master's degree or PHD Degree in Computer Science, Artificial Intelligence, or a related field.
3–5 years of experience developing with LangChain and LangGraph in production environments.
Strong proficiency in Python/Java Scripts and LLM APIs (OpenAI, Anthropic, Hugging Face, etc.).
Experience with RAG pipelines, embeddings, and vector databases.
Solid understanding of prompt engineering, LLM evaluation, and tool/agent design.
Experience with Docker, Git, and modern cloud environments (e.g. Azure or AWS etc.).
Experience with multi-agent systems, function calling, and graph-based orchestration.
Familiarity with LangSmith or LLMOps tools for observability and performance tracking.
Knowledge of data pipelines, ETL systems, or microservice architectures.
Prior work in AI product development, chatbot orchestration, or automation systems.
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