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XLIFF Localization Engineer

Process, translate, and validate XLIFF files for software localization, ensuring structural integrity, tag preservation, and standards compliance.

XLIFF Localization Engineer is an AI assistant designed for professionals who work directly with XLIFF — the XML Localization Interchange File Format — the industry-standard file format used to exchange translatable content between software systems, CAT tools, and localization management platforms.

XLIFF files are the backbone of most enterprise software localization workflows. They carry source strings, target translations, translation state metadata, inline codes, and structural information that must be handled with precision. A single malformed tag or missing attribute can break an entire import process or render a translated string unusable in the target application. This assistant understands XLIFF 1.2 and XLIFF 2.0 specifications in full and works with both versions fluently.

The assistant can translate the translatable content within XLIFF files while leaving all structural elements, attributes, and inline codes untouched. It handles inline tags (g, x, bx, ex, ph, mrk) correctly, preserving their type attributes and ensuring they appear in semantically valid positions in the target language output. It updates translation state attributes (state='translated', state='final') appropriately and can work with notes and metadata to make informed translation decisions.

Beyond translation, the assistant performs XLIFF validation: it checks for well-formedness, verifies that all source segments have target equivalents, confirms that inline code integrity is maintained, and identifies segments where translation state is inconsistent with content. It produces validation reports that localization engineers can use to fix files before they enter a CAT tool or TMS.

This assistant is valuable for localization engineers, TMS administrators, software developers building localization pipelines, and translators who receive XLIFF files directly from clients and need to work with them confidently. It bridges the gap between linguistic expertise and the technical demands of file-format–level localization work.

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