Product Manager II, Emerging Technology

Fox Corporation•Los Angeles, CA

2d•$114,000 - $152,000•Hybrid

About The Position

The Product Manager, Emerging Technology, will be responsible for defining, prototyping, and scaling next-generation AI capabilities across FOX platforms. This role is focused on emergent technologies, with an emphasis on Large Language Models (LLMs), generative AI systems, and agentic workflows. You will operate at the intersection of product strategy, applied AI, and platform development—shaping how intelligent systems are incorporated into FOX’s consumer, editorial, and monetization experiences. While this role does not require hands-on model development, it demands deep technical fluency, strong product judgment, and the ability to translate rapidly evolving AI capabilities into clear product vision and execution. You will partner closely with machine learning, data science, engineering, design, and editorial teams to identify high-impact use cases; define system requirements; and guide the development of scalable, production-grade AI-powered products. This includes systems that reason over complex inputs, orchestrate tasks across tools and APIs, and generate dynamic, context-aware outputs. This is a high-impact, high-autonomy role for a product leader energized by ambiguity, rapid prototyping, and shaping what comes next—well beyond traditional UI-driven features. Success in this role is defined by delivering intelligent, trustworthy AI systems that enhance discovery, engagement, storytelling, and operational insight—while establishing FOX as a leader in applied generative AI for media.

Requirements

Strong interest in sports, with a genuine enthusiasm for sports culture and content
5 to 8 years of product management and/or engineering experience, with a focus on platform, experimentation, or technically complex product areas
Demonstrated experience leading products that incorporate machine learning, AI, or data-driven systems in production environments
Strong conceptual understanding of Large Language Models, transformer architectures, prompt engineering, and fine-tuning approaches
Experience defining product requirements for agentic systems, including tool use, multi-step reasoning, and workflow orchestration
Familiarity with retrieval-augmented generation (RAG), embeddings, vector databases, and evaluation strategies for LLM-based products
Ability to work closely with ML engineers and data scientists to translate technical constraints into product tradeoffs and roadmaps
Comfort operating in ambiguity and making prioritization decisions amid rapid technological change
Strong analytical mindset, with experience defining success metrics and using data to guide iteration
Excellent communication skills, with the ability to align technical and non-technical stakeholders around complex ideas
Passion for the future of media, storytelling, and intelligent systems, with a strong interest in emerging AI capabilities

Nice To Haves

Experience working on AI platforms, internal tooling, or developer-facing products
Background collaborating with editorial, content, or newsroom teams
Familiarity with ethical, safety, and governance considerations in AI product development
Experience guiding teams through build vs. buy decisions for AI infrastructure
Exposure to multimodal systems combining text, audio, video, or vision
A habit of drawing inspiration from adjacent industries including media, prediction markets, fintech, et al, to inform AI-native product design

Responsibilities

Define the product vision and roadmap for AI-native capabilities, including LLM-powered systems, agentic workflows, and automated storytelling platforms
Lead early-stage prototyping efforts to validate emergent AI technologies, moving from concept to pilot with clear success metrics
Partner with machine learning and engineering teams to shape scalable architectures for training, fine-tuning, deploying, and monitoring LLM-based systems
Guide the development of agentic systems that enable models to reason, orchestrate tasks, and interact with tools, APIs, and data sources
Translate advances in generative AI, multimodal learning, and autonomous agents into practical, production-ready product capabilities
Drive experimentation and A/B testing to evaluate the impact of AI-powered features on engagement, efficiency, and business outcomes
Collaborate with editorial, content, and business stakeholders to design automated systems for storytelling, summarization, and insight extraction
Ensure AI systems meet standards for reliability, performance, safety, and observability in real-world use cases
Define and track KPIs tied to learning velocity, feature adoption, model effectiveness, and downstream business impact
Develop product requirements, briefs, and decision frameworks that align cross-functional teams around complex, evolving AI initiatives
Foster a culture of responsible innovation, curiosity, and technical rigor across product and partner teams