Senior Localization Engineer, Applied AI

Your Role

The Senior Localization Engineer, Applied AI is a pivotal technical lead role responsible for the next-generation evolution of Tenable's established multilingual delivery infrastructure. This role requires a dual focus: providing strategic architectural direction while maintaining hands‑on expertise in multilingual content engineering, system integration, and workflow automation. This is a unique opportunity to evolve our global content delivery platform — scalable and optimized for integrating AI‑led technologies — accelerating the global delivery of multilingual content across Tenable's international markets.

Reporting to the Sr Director of Globalisation, you will serve as the primary technical authority for the team, while evolving a system architecture that achieves tangible productivity outcomes through AI‑led automation.

• Lead the shift from automated to AI‑led localization:
  Lead the evolution of AI/LLM‑led workflows built for accelerated, simultaneous multi‑language releases, focusing on product UI first.
• Gradually extend the AI‑led pipeline model across the content stack:
  Take the principles proven in the product UI pipeline and, working with partner engineers, apply to other content areas — online documentation, marketing, and beyond; scale a consistent, AI‑led delivery approach across Tenable's international content ecosystem.
• Shape standards and governance:
  Define high‑standard technical best practices, system hygiene norms, and engineering documentation that the wider team can build on as you are leading through the shift.
• Build intelligence into operations:
  Complement existing reporting with AI‑powered reporting.
• Lead, build and orchestrate:
  Own hands‑on delivery of key initiatives while directing contracted and distributed engineering partners on others — with the judgment to know which work to keep close and which to delegate effectively.

• AI‑forward mindset:
  You're energized by the pace of change in AI tooling, follow new developments actively, and bring that curiosity into your engineering work.
• LLM integration:
  Hands‑on experience integrating LLMs (ideally Claude/Anthropic) and agentic steps into engineering workflows — building reliable, production‑grade AI pipelines and programmatic model improvement.
• Pipeline architecture:
  Ability to design event‑driven, API‑first translation infrastructure — where content from repos, CMS platforms, and databases flows automatically into translation engines, triggered by code commits, content changes, or release events. This also includes web and content delivery workflows such as CMS‑driven and proxy‑based localization solutions.
• Internationalization & Localization engineering:
  Strong i18n/l10n engineering awareness — string externalisation, relevant frameworks, and deep familiarity with localization file formats and encoding conventions across content types.
• Translation Management Systems:
  Solid understanding of TMS principles — Translation Memory, Machine Translation, and next‑generation integration frameworks.
• Good understanding of CI/CD and Dev Ops frameworks and principles.
• Strong scripting ability (JavaScript, Python, Regex).
• Design for scale:
  Solutions that generalise across content types and delivery channels where appropriate.
• Stakeholder communication:
  Comfortable bridging engineering and non‑engineering colleagues — linguists, project managers, developers, architects.
• Documentation discipline:
  Strong documentation habits — knowledge transfer is built into the role from day one.
• Distributed team collaboration:
  Able to work effectively with distributed teams across multiple geographies.

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