Senior Quality Manager, Applied AI
LILT, Boston, MA +5
What you will do
- Ensure Workflows Are Built for Quality
- Outcome: Every Applied AI deliverable ships with measured quality: rater agreement meets agreed thresholds per dimension, rubric scores are reproducible across raters, and reported quality figures hold up under customer audit.
- Own Technical Tooling & Quality Infrastructure
- Outcome: Quality metrics for every active program (defect rate, acceptance rate, rework, reviewer reliability, throughput, SLA adherence) are available without manual compilation, and systemic quality issues are detected from workflow data before a customer reports them.
- Own Operational Quality at Scale
- Outcome: Concurrent programs meet their quality targets within agreed cost and throughput. Acceptance rates hold at or above target, rework declines over time, and standard QC on standardized workflows is executed and interpreted by Production staff without Quality Manager involvement by the end of the second quarter in role.
- Delivery sign-off: Every deliverable has a documented go/no-go decision before shipping, based on programmatic QA and a readiness memo with flags. Post-sign-off quality escapes stay below an agreed threshold, and each escape results in a documented process change.