SECAI Core · phase 9 of 15
MLOps engineer
A role that automates the lifecycle on the platform by establishing continuous integration and delivery for AI models and prompts, managing versioning and lineage, orchestrating retraining workflows, and setting up monitoring
The Explain card
- Plain English
- An MLOps engineer automates the AI lifecycle on the platform: continuous integration and delivery for models and prompts, versioning and lineage, retraining workflows, and monitoring.
- Example
- They build a pipeline where every change to a prompt template or model weights is versioned, tested against an evaluation suite, and deployed only if it passes. Lineage records show exactly which data and code produced each model in production.
- Why it matters
- Lineage and versioning are how defenders answer "which model was live when that happened?" and roll back a poisoned or misbehaving version fast.
- Hook
- CI/CD for models, with a receipt for every version.
Where it sits in the deck
Phase 9: Roles, Teams, and Organisational Accountability
Governance frameworks are executed by people — introduce the human roles and organisational structures responsible for building, operating, and auditing AI systems.
