At a Glance
- Tasks: Ensure high-quality AI-generated content and curate a dynamic use-case library.
- Company: Join Multiverse, an innovative startup within a leading enterprise.
- Benefits: Flexible work environment, competitive salary, and opportunities for professional growth.
- Other info: Thriving startup culture with a focus on continuous improvement and innovation.
- Why this job: Be at the forefront of AI content development and make a real impact.
- Qualifications: Strong editorial judgment and hands-on AI skills required.
The predicted salary is between 45000 - 60000 £ per year.
Adopt is Multiverse’s newest bet: an AI adoption platform that helps every employee at our enterprise customers answer what they really do with AI in their job. It delivers role‑specific playbooks, use cases, and resources that surface at the moment of need. Adopt runs as a startup inside the business. We’re shifting from a manually curated content process to one where AI generates the majority of content at a scale no human team can match. By year end we aim to support large enterprise deals and thousands of learners and use cases, so the systems and the people guarding their quality must be excellent.
The AI Content Specialist is the human in the loop who ensures AI‑generated content is high‑quality and trustworthy. You’ll own the quality and currency of the use‑case library, review what’s created, identify shortcomings, keep content accurate as tools change, and curate the knowledge bases that our AI models use. This role is suited to someone energized by working with AI‑generated content at scale, with the instincts of a strong content developer, and who cares more about whether content works than about authoring it from scratch. It is an individual contributor position reporting to the Director of Learning for Adopt.
Key Responsibilities
- Quality‑assure AI‑generated content: review a sample of use cases produced by our AI content generation system for accuracy, prompt quality, realistic outputs, and credible time savings. Act as the human judgment layer on top of automated checks.
- Improve the system: identify patterns where generation falls short and feed insights back to the AI Content Systems Architect, driving continuous improvement.
- Keep content current: use an AI‑assisted process to identify use cases affected by tool changes and update them so the library remains accurate.
- C curate the knowledge base: maintain generic and customer‑specific knowledge bases of best practices and AI tool documentation, ensuring accuracy and proper tagging.
- Support governance and feedback: triage user feedback, route it appropriately, and act on it; support reviewers on quality standards.
Success Metrics
- Content accuracy and quality: sampled content meets the quality bar with low user‑reported issues.
- Content effectiveness: use cases lead to real‑world application and impact stories.
- Content currency: the library stays up‑to‑date with minimal trust‑eroding errors.
- System improvement: QA insights demonstrably improve content generation quality over time.
- Knowledge base health: the generic knowledge base and resource library are accurate, current, and well‑tagged.
Skills & Qualifications
- We’re looking for a blend of editorial judgment and hands‑on AI fluency.
- Editorial judgment & quality instinct: quickly assess accuracy, usefulness, and adherence to the quality bar, with strong attention to detail.
- Hands‑on AI building skills: use AI coding tools (Claude, Cursor) to build end‑to‑end front‑ends or agents without engineering support; navigate GitHub, submit pull requests, etc.; have a portfolio of small projects.
- Evals fluency: understand structured AI‑output evaluation, design simple rubrics, and explain how to use them to catch quality problems at scale.
- Bias toward effectiveness over volume: value applied learning and content that changes work behaviour.
- Rigour & data fluency: analyze data to track quality trends, identify insights, and prioritize focus areas.
- Bias to action & comfort with ambiguity: launch imperfect solutions in a startup environment, right‑size effort, and adapt as the product evolves.
Bonus Experience
- Experience in learning design, instructional design, content strategy, or technical writing/editing.
- Experience designing for or working in technical or AI disciplines.
- Prior exposure to LLM evaluation tooling or platforms beyond foundational fluency.
AI Content Specialist - Adoption in London employer: The Digital Asset Management Consortium, Inc.
At Vet Partners, we pride ourselves on being an exceptional employer that fosters a collaborative and innovative work culture in the heart of York. Our commitment to employee growth is evident through tailored training programs and opportunities to engage with cutting-edge AI technologies, ensuring that our team members are equipped to excel in their roles. With a focus on work-life balance and a supportive environment, we empower our employees to contribute meaningfully to our mission of delivering high-quality document governance and information management solutions.
Contact Details:
The Digital Asset Management Consortium, Inc. Recruitment Team
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