GenAI ML Engineer: Build Production-Grade AI Pipelines

Stellar Technologies; Abu Dhabi; On-site; AED 260,000 - 480,000; Full time

Job summary

Stellar Technologies is seeking a Machine Learning Engineer (GenAI) to design, build, and deploy next-generation AI systems leveraging LLMs, RAG, and agentic AI frameworks. You will bridge model development and production engineering to deliver scalable, production-ready AI capabilities for enterprise platforms.

Join a collaborative team of engineers and data scientists, working across cloud infrastructure, model deployment, and real-time APIs to drive governance, performance, and cost

Qualifications

• Strong hands-on experience with LLMs, RAG, and agentic frameworks.

Responsibilities

• Develop and optimize AI systems leveraging LLMs, RAG, and agentic frameworks.
• Build production-grade ML pipelines with real-time inference and retrieval components.
• Design and manage APIs and streaming services to integrate models into enterprise platforms.
• Implement containerized deployments using Docker, Kubernetes, and Azure ML.
• Automate data preprocessing, model training, evaluation, and versioning.
• Collaborate with cross-functional teams to integrate models into front-end and analytics workflows.
• Ensure governance, compliance, and security of deployed AI workloads.
• Monitor AI systems in production using observability frameworks.
• Participate in architecture discussions to improve scalability and reliability.

Skills

LLMs, RAG & agentic frameworks

Python & ML libraries (PyTorch, Tensor

API & microservices engineering

Streaming architectures & real-time

Azure cloud & ML Ops

Containerization & orchestration (Dock

Vector databases & retrieval (Pinecone

CI/CD & production monitoring

Tools

Docker

Kubernetes

Azure ML

Job description

Stellar Technologies is seeking a Machine Learning Engineer (GenAI) to design, build, and deploy next-generation AI systems leveraging LLMs, RAG, and agentic AI frameworks. You will bridge model development and production engineering to deliver scalable, production-ready AI capabilities for enterprise platforms.

Join a collaborative team of engineers and data scientists, working across cloud infrastructure, model deployment, and real-time APIs to drive governance, performance, and cost