Localization Lead, Engineering & Automation

Requirements

• Automation & data engineering. Hands-on background in automation, workflow orchestration, internal tooling, or data engineering, including scripting, working with APIs, connecting disparate systems, and building reliable operational workflows. Experience with tools such as n8n, Apache Airflow, or similar platforms is an asset.
• Language technology domain. Direct experience in the language technology ecosystem, such as a CAT/TMS environment (e.g., memoQ, Phrase, RWS/Trados, Smartcat), a machine translation or language AI platform, or a technical role within an LSP with hands-on involvement in translation workflows.
• Translation memory & terminology leverage. Strong understanding of how TM leverage, fuzzy matching, and terminology management drive productivity, consistency, and quality, enough to set direction, prioritize asset-quality work, and be accountable for measurable gains. Hands-on linguistic engineering is not required, but the judgment to direct it is.
• Translation workflow fluency. Working knowledge of professional translation workflows, including intake, project setup, pre-translation, MTPE, revision, QA, delivery, and production reporting.
• Integration & APIs. Practical experience designing, improving, or operating integrations between systems, including API design, integration patterns, data flow, and monitoring.
• Team leadership. Experience leading or managing a technical or cross-functional team, such as engineering, automation, solutions engineering, localization engineering, data, analytics, or internal tooling.
• Operational delivery mindset. Ability to work directly with operational teams, understand real production workflows, separate quick wins from deeper structural work, and deliver solutions that are adopted in practice.

Preferred