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Ai product manager

Dublin
Storyful
Product manager
€104,000 - €130,878 a year
Posted: 12 September
Offer description

Storyful is an equal opportunity employer

Job Description
Role: AI Product Manager

Location: Dublin, Ireland

Type: Full-time

Hybrid - 3 days in the office

________________________________________

About Storyful
Storyful, a News Corp company, is a global leader in social media news and intelligence. We provide trusted, verified eyewitness content, digital context, and strategic insights to the world's largest newsrooms, broadcasters, digital platforms, and brand teams.

At Storyful, our mission is clear: protect truth in a world where misinformation spreads faster than facts.

What We Are Looking For
We're looking for an AI Product Manager who is as curious as they are detail-oriented — someone who thrives on building fast prototypes, obsesses over customers, and believes action is the best way to learn. You'll join a team at the crossroads of journalism and AI innovation, turning emerging technologies into products that strengthen trust, empower decision-makers, and help organizations everywhere navigate risk with confidence. If you're driven by purpose and excited to shape how truth is protected in the digital age, this is your chance.

Day to day, you'll be working directly with customers and partnering across teams — from engineering and design to editorial and commercial — to turn complex problems into simple, impactful solutions. Clear communication will be at the heart of everything you do: aligning diverse perspectives, articulating priorities, and making sure everyone is moving in the same direction. You'll rely on evidence, research, and real user feedback to guide your decisions, thriving in an environment where learning fast and iterating often is the path to building products that truly matter.

This isn't backlog babysitting. This is about shaping how AI drives measurable business and customer outcomes. You'll own the strategy, prototyping, and delivery of AI-powered products that move the needle on activation, retention, and cost-to-serve.

We bias to action: prototype → learn → scale. You'll test ideas in days, not months, and prove value before we double down. You'll be the connective tissue between research, design, engineering, and commercial — translating messy problems into AI solutions

Who You Are

* You have a love of making things real, fast, you'll spin up prototypes in Replit, Colab, or a notebook before most people have finished a spec.
* You're data-obsessed, guided by insights, experiments, and evidence rather than assumptions.
* You geek out on Jobs to Be Done, you want to deeply understand why people hire (or fire) a product and build around that.
* You're a problem-solver at heart, messy workflows, ambiguous briefs, gnarly datasets: you lean in, not out.
* You're restlessly curious, always testing new model patterns, growth levers, and evaluation frameworks to expand what's possible.
* You're outcome-driven, shipping only matters if it moves the metric. You align everything back to OKRs.
* You thrive on rapid learning loops, prototype, test, learn, iterate — and know alignment beats perfection.

What You'll Do

* Activate the strategy: Collaborate with the product team to define Define an AI roadmap tied directly to company OKRs (activation, retention, revenue, cost-to-serve).
* Prototype fast: Spin up low-fidelity builds to validate assumptions before we invest in production.
* Turn insights into impact: Translate JTBD and user research into PRDs for copilots, workflow agents, and AI-augmented analytics.
* Run discovery sprints: Drive A/B tests, shadow launches, and evaluation loops (quality, latency, cost).
* Scale what works: Partner with engineering to productionise validated prototypes, optimising for reliability, performance, and cost efficiency
* Champion responsible AI: Partner with Legal/Sec/Privacy to embed safety, audit trails, and governance into every build.
* Monitor what matters: Implement runtime observability for drift, hallucinations, and safety events, and tie outcomes to KPIs.

What Success Looks Like (6–12 months)

* Adoption: Launch 2–3 AI experimentation features with >30% adoption in test cohorts, with at least one scaling to GA and achieving 40%+ adoption.
* Efficiency: Deliver validated experiments showing 15–20% task-time or cost-per-task reduction, creating a path to 25%+ efficiency gains at scale.
* Reliability: Stand up evaluation and guardrail pipelines so hallucinations, drift, and safety incidents remain within agreed thresholds.
* Learning Velocity: Run 3–4 validated experiments per quarter, establishing a repeatable prototype-to-production loop that compounds insights every sprint.
* Impact: Demonstrate measurable lifts in activation, retention, and analyst efficiency — tying every experiment back to OKRs and showing a clear line from prototype to business outcome.

What You'll Bring

* 5–8+ years in product management (at least 2 in AI/ML; GenAI strongly preferred).
* Fluent in LLM app patterns (RAG, agents/tool use, fine-tuning, function calling) and their trade-offs.
* Experience with growth and experimentation stacks (Amplitude, Mixpanel, GrowthBook, Optimizely, LaunchDarkly, Collab).
* Comfortable co-designing prompts, eval sets, and cost/latency budgets with Eng/DS.
* Strong communicator; ruthless prioritiser; excellent at stakeholder alignment.

AI Tools & Stack (Indicative of the role)

* Models: OpenAI, Anthropic, Google, Meta
* Frameworks: LangChain, LlamaIndex
* Vector DBs: pgvector, Pinecone, Weaviate
* Evaluation: LangSmith, RAGAS, Promptfoo
* Observability: Arize, Phoenix
* Orchestration: Airflow, Prefect
* Feature Flags: LaunchDarkly
* Analytics/BI: Amplitude, Mixpanel, dbt, Looker, Mode, GA

Job Category
Storyful - Product & Technology

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