AI Engineer – AI Ops (Monitoring AI Systems in Production)

About the role

We are looking for an AI Engineer specialized in AI Ops to ensure that AI models and agent‑based systems run reliably in production. You will bridge the gap between model development and sustainable, monitored deployment, keeping performance, compliance and business impact in check.

Key responsibilities

• Monitor AI models and agents in production for performance, latency, errors and availability.
• Track health indicators such as model drift, data distribution changes and output stability, and link them to business KPIs.
• Detect, triage and recover from production incidents, executing rollbacks or throttling when thresholds are breached.
• Support deployment, versioning and release of models using CI/CD‑style pipelines and maintain model registries with ownership, lineage and risk metadata.
• Ensure compliance with Responsible AI principles, maintain audit trails and support fairness, bias and explainability monitoring.
• Integrate AI systems with monitoring, logging and alerting platforms, and work with cloud infrastructure (containers, event streaming, APIs) to enable scalable operations.
• Collaborate with product, engineering, data science and risk teams to standardise AI Ops patterns.

Required profile

• Strong Python programming skills and experience with ML or LLM‑based systems.
• Solid understanding of Model Ops / MLOps, especially the operational phase after deployment.
• Proven ability to work cross‑functionally with product, data science, engineering and risk teams.

Required skills

• Python
• Monitoring and logging systems
• CI/CD pipelines
• Containerised deployments (Docker)
• Azure cloud platform
• Production troubleshooting