Senior AI Engineer

About the role

We're looking for a Sr AI Engineer who has shipped AI products, not just prototyped them, with equal footing in core ML and modern GenAI. This role sits at the intersection of engineering rigor and product ownership, you'll build, deploy, and operate ML and LLM-powered applications on Azure, with real accountability for what happens after go-live: accuracy, cost, latency, safety, drift, and uptime.

What you'll do

• Own end-to-end deployment of AI applications on Azure — from classical ML models and Azure OpenAI Service integrations through to production release, monitoring
• Build and evaluate core ML models where GenAI isn't the right tool — classification, regression, forecasting, clustering
• Design and implement guardrails — content filtering, prompt injection defence, PII redaction, output validation, and human-in-the-loop checkpoints for high-risk actions
• Build and maintain MLOps/LLMOps pipelines — CI/CD for models and prompts, feature engineering and data pipelines, automated evaluation harnesses
• Manage the model lifecycle — model selection and routing (classical ML vs. smaller LLMs vs. frontier models by task complexity and cost), performance benchmarking

What you need

• Machine learning
• LLMs
• Scikit-learn
• Pandas
• Python
• MLOps

Good to have

• Deep learning
• NumPy
• PyTorch
• TensorFlow
• Azure
• CI/CD