Manager, Software Engineering, AI Solutions

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.

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• Consumer AI Features: Expand and iterate on consumer-facing AI features (article summaries, content classification, product classification/summarization, weather summaries) with a focus on accuracy, reliability, and editorial standards
• Brand Safety Classification: Complete the transition from a vended, rules-based brand safety system to an in-house LLM-based classification product that is already outperforming the incumbent-positioning CNN to scale classification to live streams and deliver unified content classification across the organization
• Internal AI Tooling: Build AI-assisted workflows for editorial, product, design, engineering, and business teams-including tool provisioning, training, and adoption programs (e.g., Claude Code)
• AI Platform Stewardship: Manage the current AI platform (prompt management, evaluation, caching, versioning, deployment, tenant management) through its evolution toward ML Foundations ownership
• Foundation Model Integration: Evaluate, select, and govern foundation model usage; build use case-specific prompt engineering UIs; monitor AI feature accuracy and performance

• Support, coach, mentor, and provide valuable feedback to the individuals you manage to help them excel-across a range of roles including software engineers, applied AI specialists, and potentially additional disciplines as the team grows.
• Work with cross-functional partners and stakeholders on activities such as planning, technical strategy, quality, and delivery.
• Partner with engineers within the team and across the organization to build, operate, and iterate on AI-powered features and internal AI tools, ensuring accuracy, reliability, and trustworthiness standards appropriate for a news organization.
• Partner with product, editorial, and business teams on feature requirements, accuracy standards, and user feedback-serving as the connective tissue between AI capabilities and CNN's user-facing and internal products.
• Partner with Machine Learning, ML Platform, and Data Platform teams for model approach decisions, deployment infrastructure, and production data access.
• Work closely with the Senior TPM to manage intake, delivery, and cross-team coordination as the portfolio of AI features and tools expands.
• Lead other engineers on the team by example, code reviews, and coaching, ensuring that code is readable, maintainable, scalable, observable, and resilient.
• Champion improvements to developer experience, integrations, and testing processes.
• Leverage vended and open-source cloud technologies to reduce maintenance costs and improve efficiencies, ensuring our products remain cost-effective.
• Build and scale the team through hiring, onboarding, and establishing team norms for a rapidly growing group

• Review and provide guidance on production-quality code that adheres to industry standards and best practices (IaC, CI/CD, etc.)
• Demonstrate a passion for AI-powered product development, with a strong sense of responsibility for the quality and accuracy of what your team ships.
• Take ownership of issues and be a strong advocate for your team and the products.
• Embrace failure as a learning opportunity-use research and experimentation to ultimately choose the best solutions that meet company goals.
• Follow a progressive development methodology, moving from proof-of-concept to prototype to production release.
• Enhance the effectiveness of your team and our partners by sharing your knowledge, communicating about complex AI technologies and problems in simple terms, and driving technical decisions.
• Collaborate across functions, squads, teams, and organizations to best serve our users.

• 8+ years of progressively complex experience designing, building, and shipping products.
• 5+ years of experience managing engineering teams, as well as, software engineering experience building production applications, ideally including AI/ML-powered features.
• 3+ years of experience with cloud infrastructure, deployment pipelines, and production systems.
• Experience leading engineers who build applications that integrate ML models and/or foundation models (LLMs, GenAI).
• Familiarity with GenAI application patterns-prompt engineering, evaluation frameworks, foundation model integration, RAG, caching, and cost management.
• Familiarity with experimentation frameworks and A/B testing methodologies.
• A proven track record of building web-scale products that are highly available and performant.
• Passion for growing engineers through mentorship, talent acquisition, and professional development.
• Experience scaling teams-hiring, onboarding, and establishing culture and processes for a growing group.
• A collaborative mindset, understanding that great results come from teamwork and a positive culture.
• Proven success leading complex projects within an engineering team: knowing when to handle issues independently, when to rally the right people for alignment, and when to escalate.
• Comfort navigating ambiguity in a fast-evolving space-GenAI best practices are still being established.
• Excellent communication, presentation, and documentation skills

• Experience building consumer-facing GenAI features in production.
• Experience with LLM evaluation, prompt versioning, or AI content quality measurement.
• Experience building internal developer tools or productivity tooling.
• Familiarity with content classification, summarization, or NLP applications.
• Experience in a news, media, or content-heavy environment where accuracy and trust are paramount