Applied AI Specialist

** _Welcome to Warner Bros. Discovery... the stuff dreams are made of._*
* ** Who We Are...*
* When we say, "the stuff dreams are made of," we're not just referring to the world of wizards, dragons and superheroes, or even to the wonders of Planet Earth. Behind WBD's vast portfolio of iconic content and beloved brands, are the  _storytellers_  bringing our characters to life, the  _creators_  bringing them to your living rooms and the  _dreamers_  creating what's next...

From brilliant creatives, to technology trailblazers, across the globe, WBD offers career defining opportunities, thoughtfully curated benefits, and the tools to explore and grow into your best selves. Here you are supported, here you are celebrated, here you can thrive.

We are the now and the next. The power behind the people building the future. We are born from the spirit of innovation. We are created from the idea that people around the world want more, need more, deserve more. We are the home of the global digital revolution. We are CNN.

To see what it's like to work at CNN, follow @WBDLife on  Instagram ()   and  X ()  !

With deep domain expertise, advanced technical capabilities, and a proven track record of successful collaborations, the AI Enablement & Machine Learning team at CNN is accelerating our digital transformation through strategic applications of machine learning and AI technologies.

The AI Systems & Enablement group within this team builds and operates AI-powered applications for CNN 's audiences and internal teams, and drives AI adoption across the organization through tool governance, training, and enablement programs. Current products include article summaries, content and product classification, weather summaries, and brand safety classification. The team also leads CNN 's AI enablement efforts - including AI Practices Guild leadership, Claude Code rollout, foundation model governance, and productivity measurement.

Our vision is that CNN delivers AI-powered features that enhance user experience and internal productivity with systems that are reliable, accurate, and trustworthy - meeting the high standards our audiences expect from a news organization - while equipping the broader organization with the tools, governance, and skills to work effectively with AI.

** Your New Role...*
* The Applied AI Specialist is a non-traditional Business Analyst role within the AI Systems workstream, reporting to a Software Engineering Manager. Rather than traditional requirements gathering and process documentation, this role focuses on the critical intersection of AI capabilities and CNN 's content, editorial standards, and product experiences. You will be hands-on with our AI-powered features - designing and refining prompts, building evaluation frameworks, structuring human feedback workflows, and working directly with engineering and editorial partners to ensure AI outputs meet CNN 's standards for accuracy and trustworthiness.

This role is ideal for someone with deep knowledge of content operations, editorial standards, or content classification - combined with a strong understanding of how AI and large language models work. You will work alongside software engineers who handle code, infrastructure, and optimization. Your focus is on the quality, accuracy, and appropriateness of what our AI features produce.

Key areas you will work on

** Prompt Engineering:
** Design, build, iterate on, and maintain prompts for production AI features including article summaries, content classification, brand safety classification, and new features as they launch. Develop and document prompting patterns and templates that can be reused across projects.

** Evaluation & Quality:
** Design evaluation criteria and workflows for AI features. Define what "good" looks like for each use case, build evaluation datasets, run quality assessments, and track accuracy over time. Identify when and where AI outputs need human review.

** Human-in-the-Loop Workflows:
** Design and execute workflows for human feedback on AI outputs. Determine when human intervention is necessary, structure how that feedback is systematically captured, and work with ML and engineering partners to feed it back into prompt and model improvement cycles.

*
* Cross-Functional Collaboration:

** Partner closely with engineers on your team who own the technical implementation of AI features, as well as editorial stakeholders on assigned projects. Help translate AI capabilities and limitations into terms that inform feature decisions and editorial guidelines. Communicate what's feasible, what the tradeoffs are, and what's needed to improve quality for specific use cases.

** Your Role Accountabilities...*
* + Own the prompt engineering lifecycle for assigned AI features - from initial design through iteration, testing, and production maintenance

+ Build and maintain evaluation frameworks that measure AI output quality against CNN 's editorial and accuracy standards

+ Design and run human review workflows, ensuring…