AI Engineer – Agentic & Generative AI (m/f/d)

Halian | Managed Services, Recruitment and Contract Staffing Agency; Abu Dhabi; On-site; AED 300,000 - 420,000; Full time

Job summary

Halian is seeking an AI Engineer to design, implement and deploy Agentic and Generative AI solutions in a major digital transformation initiative. You will own production-grade RAG pipelines, LLM fine-tuning with LoRA/QLoRA, Python-based services, and tool integrations across enterprise systems.

You will work closely with AI, data, engineering and product teams to translate complex requirements into robust AI capabilities, ensuring safety, performance and reliability in production environments.

Qualifications

• Hands-on implementation of AI agents or agentic workflows in real-world applications.
• Must have personally fine-tuned LLMs using LoRA and/or QLoRA. This is a core requirement.
• Must have personally built and deployed Retrieval-Augmented Generation solutions into production, including embeddings, retrieval and vector databases.
• Strong and hands-on Python development for AI/ML applications and production systems.
• Approximately 3-5 years of hands-on AI/ML engineering experience, ideally within ~6 years of overall professional experience.

Responsibilities

• Design and implement Agentic AI workflows, including tool/function calling, orchestration, automated decision flows and system integrations.
• Build and deploy production-grade RAG pipelines, covering document ingestion, chunking, embeddings, vector search, retrieval and grounded generation.
• Fine-tune LLMs using LoRA and/or QLoRA, including dataset preparation, training, evaluation and optimization.
• Develop production AI applications and services using Python.
• Integrate LLMs and AI agents with APIs, enterprise systems and data sources.
• Implement evaluation frameworks and guardrails to measure model accuracy, quality, safety and reliability.
• Containerize and deploy AI services using Docker, REST APIs, CI/CD and cloud platforms.
• Monitor production AI systems for performance, latency, model quality and drift.
• Collaborate with AI, data, engineering and product teams to turn complex requirements into working AI capabilities.

Skills

Agentic AI

LLM Fine-Tuning

Production RAG

Python

AI/ML Engineering

Tools

Python

LangChain

LangGraph

LlamaIndex

Hugging Face Transformers

PEFT

LoRA

QLoRA

RAG

Vector Databases

PyTorch

TensorFlow

REST APIs

Docker

CI/CD

AWS

Azure

GCP

Job description

About The Role

We are looking for a hands-on AI Engineer to help build and implement next-generation Agentic AI and Generative AI solutions for a major digital transformation initiative.

This is an engineering-focused role for someone who has gone beyond experimentation and has personally built, fine-tuned and deployed AI solutions into production. You will work extensively across Agentic AI, LLM fine-tuning, RAG, Python and production AI engineering.

What You'll Be Doing

• Design and implement Agentic AI workflows, including tool/function calling, orchestration, automated decision flows and system integrations.
• Build and deploy production-grade RAG pipelines, covering document ingestion, chunking, embeddings, vector search, retrieval and grounded generation.
• Fine-tune LLMs using LoRA and/or QLoRA, including dataset preparation, training, evaluation and optimization.
• Develop production AI applications and services using Python.
• Integrate LLMs and AI agents with APIs, enterprise systems and data sources.
• Implement evaluation frameworks and guardrails to measure model accuracy, quality, safety and reliability.
• Containerize and deploy AI services using Docker, REST APIs, CI/CD and cloud platforms.
• Monitor production AI systems for performance, latency, model quality and drift.
• Collaborate with AI, data, engineering and product teams to turn complex requirements into working AI capabilities.

Must-Have Technical Experience

We are specifically looking for candidates who can demonstrate:

• Agentic AI: Hands-on implementation of AI agents or agentic workflows in real-world applications.
• LLM Fine-Tuning: Must have personally fine-tuned LLMs using LoRA and/or QLoRA. This is a core requirement.
• Production RAG: Must have personally built and deployed Retrieval-Augmented Generation solutions into production, including embeddings, retrieval and vector databases.
• Python: Strong and currently hands-on Python development for AI/ML applications and production systems.
• AI/ML Engineering: Approximately 3-5 years of hands-on AI/ML engineering experience, ideally within approximately 6 years of overall professional experience.

Technical Stack

Experience across a combination of:

Python | LangChain | LangGraph | LlamaIndex | Hugging Face Transformers | PEFT | LoRA | QLoRA | RAG | Vector Databases | PyTorch | TensorFlow | REST APIs | Docker | CI/CD | AWS | Azure | GCP

AI Engineer - Agentic & Generative AI in Abu Dhabi, United Arab Emirates