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

About The RoleWe 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 DoingDesign 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 ExperienceWe 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 StackExperience 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 | GCPAI Engineer – Agentic & Generative AI in Abu Dhabi, United Arab Emirates