Artificial Intelligence Engineer

We are seeking an MLOps / AI Engineer to bridge the gap between experimental data science and production-grade systems. This role sits at the core of building scalable AI solutions, with a strong focus on LLMs, agentic workflows, and end-to-end ML pipelines.

You’ll work across the full lifecycle from concept to deployment partnering with data scientists, engineers, and infrastructure teams to deliver production-ready AI systems.

What You’ll Do

• Design, build, and deploy end-to-end machine learning pipelines
• Operationalise LLMs, embeddings, and multi-agent systems in real-world environments
• Develop and maintain scalable data pipelines and model lifecycle workflows (training, validation, deployment)
• Build production-grade RAG systems and AI-driven applications
• Manage model performance, monitoring, and data drift in production
• Containerise applications using Docker and deploy via Kubernetes
• Build and maintain CI/CD pipelines for ML and AI applications
• Collaborate with data scientists to translate research into production-ready systems

What We’re Looking For

• Strong Python programming skills (clean, scalable, production-level code)
• Hands-on experience with LLMs and modern AI frameworks
• Solid understanding of MLOps (MLflow or similar tools for tracking and registry)
• Experience with Docker and working knowledge of Kubernetes
• Experience building and deploying ML pipelines end-to-end
• Exposure to agentic workflows, LLM orchestration, or reasoning frameworks
• Familiarity with CI/CD tools such as GitLab or Jenkins
• Strong foundation in machine learning concepts (model evaluation, optimisation, etc.)

Nice to Have

• Experience with GPU optimisation and cloud-based ML workloads
• Background in building scalable AI platforms or infrastructure

Why This Role

• Work on production-grade AI systems, not just experimentation
• Exposure to advanced LLM and agent-based architectures
• Opportunity to build across multiple AI use cases and environments
• Strong collaboration across engineering, data, and business teams

If you’re interested, feel free to apply or reach out directly for a confidential discussion.