Senior MLOps (AI Platforms / LLM Systems)

About This Role

General Description

Join a fast-growing, AI-driven organization in Abu Dhabi building next-generation AI platforms and intelligent systems at scale.

The organization focuses on delivering enterprise-grade AI ecosystems , combining AI/ML, cloud infrastructure, and data platforms to power large-scale digital transformation initiatives across enterprise and government environments. Their work centers on building production-ready AI platforms , including LLM-based systems, intelligent automation, and scalable AI infrastructure.

We are looking for experienced MLOps / AI Platform Engineers (Senior / Lead level) to design, build, and scale production-grade AI and machine learning platforms. This role focuses on delivering end-to-end AI systems, including LLM-based applications, ML workflows, and backend services that power enterprise and large-scale AI use cases.

This role is ideal for engineers with strong experience in AI/ML systems, backend development, and cloud infrastructure , who can bridge the gap between model development and real-world production deployment.

This is a 6-month contract role (extendable) with full onsite presence in Abu Dhabi .

Key Responsibilities

• Design and build scalable AI platforms supporting ML workflows and LLM-based applications
• Develop and deploy AI/ML models into production environments using MLOps best practices
• Build and maintain backend services and APIs (Python, FastAPI) for AI-powered systems
• Implement and optimize RAG pipelines and LLM-based solutions using tools like LangChain and LlamaIndex
• Manage containerized deployments using Docker and Kubernetes in cloud environments (AWS/Linux)
• Establish and maintain CI/CD pipelines for ML and AI workloads (Jenkins, Terraform, DVC, MLflow)
• Implement model serving and orchestration using tools such as KServe
• Work with vector databases and data systems (FAISS, PostgreSQL, Redis) to support AI applications
• Monitor system performance, reliability, and observability using Prometheus and Grafana
• Collaborate with cross-functional teams including AI/ML engineers, backend developers, and platform teams to deliver high-quality AI systems.

Required Skills & Experience

• Strong experience as an MLOps Engineer, AI Platform Engineer, or Backend Engineer with AI/ML exposure
• Proven experience deploying ML models or AI systems into production (not just experimentation)
• Hands-on experience with LLMs, RAG pipelines, or GenAI-based applications
• Strong programming experience in Python with backend frameworks such as FastAPI
• Experience with containerization and orchestration (Docker, Kubernetes)
• Experience working in cloud environments (AWS or similar) and Linux systems
• Familiarity with MLOps tools such as MLflow, KServe, DVC, Jenkins, or Terraform
• Experience working with data systems, vector stores, and caching layers (PostgreSQL, Redis, FAISS)
• Understanding of monitoring, logging, and observability tools (Prometheus, Grafana)
• Experience working in scalable, distributed systems and microservices architectures.

Engagement Details

Engagement Type: Contract / Freelance

Duration: 6 months (extendable)

Location: Abu Dhabi (Full Onsite)