Data & AI Operations Engineer

Role Overview

Apply AI/ML/LLM tools to solve operational and reliability challenges, prototype and validate AI-driven improvements, and operationalise successful AI use cases into scalable production systems.

What You Will Do

Enhance observability, incident detection, and automation in operations, support end-to-end lifecycle of AIOps, MLOps, and LLMOps solutions, and automate repetitive tasks with scripts/workflows.

Why It Might Be a Fit

Stay ahead of emerging AI technologies, embed responsible AI practices, and collaborate with engineers and ops teams to align solutions with business needs.

Requirements

• Bachelor’s/Master’s in Computer Science or related field
• 1–2 years’ experience with Python, SQL, Spark, Docker/Kubernetes, Git, pytest
• Exposure to MLOps/GenAI Ops tools, ML/GenAI projects, or open-source contributions
• Familiarity with monitoring stacks (Prometheus, Grafana, OpenTelemetry)
• Hands-on with cloud ML services (Databricks, Azure ML, etc.)