Research Product Manager AP Intelligence

Associated Press•New York, NY

4d•$140,000 - $185,000•Remote

About The Position

The Associated Press is seeking an intellectually curious, highly analytical Research Product Manager to lead research and product definition for emerging AP Intelligence capabilities. This is a 0→1 individual contributor role. Much of the work begins before there is a roadmap—and sometimes before the precise product problem is fully understood. You will turn broad questions into structured hypotheses, research plans and experiments; investigate them using data, customer conversations and lightweight prototypes; and translate what you learn into clear product decisions and requirements. Here, “research” means structured product investigation: framing unanswered questions, working directly with data and product outputs, testing hypotheses, evaluating results and learning from customers. This is not a traditional feature-delivery PM role. You will help discover the problems, define the products and establish the frameworks that allow engineering teams to build them. The role does not have direct reports at the outset, but offers significant ownership and visibility. As AP Intelligence grows, its scope may expand based on business needs and the individual’s strengths and interests, including deeper product leadership, domain ownership or people leadership.

Requirements

6+ years of relevant professional experience, including significant experience in product management, data products, AI/ML products, applied research, search/information systems or another highly analytical product environment.
A strong track record of taking ambiguous problems and independently turning them into structured questions, experiments and product recommendations.
Exceptional analytical and conceptual thinking, with an ability to find patterns in complex information and develop clear points of view from incomplete evidence.
Strong technical and data fluency. You do not need to be a production engineer, but should be comfortable exploring datasets, interrogating outputs and building lightweight analyses or prototypes.
Familiarity with structured or semi-structured data and areas such as APIs, taxonomies, ontologies, knowledge graphs, search, retrieval or related information systems.
Working knowledge of modern AI systems and concepts, including LLMs, RAG, embeddings, information retrieval, structured outputs and model evaluation.
Strong product and customer judgment, including the ability to distinguish an interesting research problem from a capability customers will use and value.
Excellent written and verbal communication skills and comfort working across engineering, AI, journalism, commercial teams and senior leadership.

Nice To Haves

Experience with AI/ML products, knowledge graphs, search/retrieval, real-time or event-driven data, intelligence platforms, AI evaluation, financial/risk/geopolitical information products, or early-stage 0→1 environments is especially relevant, but not required.

Responsibilities

Lead research into ambiguous product questions across event intelligence, structured news data, knowledge graphs, real-time information and AI systems.
Turn questions such as “What makes an event important?” or “How should we measure whether a signal is reliable and useful?” into hypotheses, experiments and evaluation frameworks.
Work hands-on with AP datasets and product outputs, using tools such as SQL, Python, notebooks, LLMs and lightweight prototypes to test ideas.
Design benchmarks and evaluation methods for dimensions such as accuracy, timeliness, confidence, relevance and usefulness.
Identify patterns that can become scalable schemas, taxonomies, scoring systems and product capabilities.
Translate research into clear product concepts, requirements and recommendations engineering teams can build.
Define how concepts such as event importance, impact, velocity, provenance and confidence become useful AP Intelligence capabilities.
Partner with engineering and applied AI teams to identify failure modes, improve product quality and move promising ideas from prototype to production.
Use evidence to recommend which ideas should advance, change or stop and to inform AP Intelligence priorities.
Work directly with prospective customers and design partners to understand workflows, test emerging concepts and determine where AP Intelligence creates meaningful value.
Assess not only whether a capability is technically possible, but whether customers will integrate it, rely on it and pay for it.
Partner closely with journalists, engineers, AI teams, commercial teams and senior leaders.
Synthesize editorial, technical, customer and commercial perspectives into clear decisions and communicate complex ideas to technical and nontechnical audiences.