Senior Product Director, Agentification, Skills and Data
WPP is hiring a Senior Product Director, Agentification, Skills and Data in London, United Kingdom. Level rates it ; you can apply on Level.
AI in this role
WPP is the trusted growth partner for the world’s leading brands.
We unite cutting-edge media intelligence and data solutions, world-class creativity, next-generation production, transformative enterprise solutions and expert strategic counsel in a single company – powered by exceptional talent and our agentic marketing platform, WPP Open, to help our clients navigate change, capture opportunity and deliver transformational growth.
We work with the world's most valuable brands and have global reach across 100+ markets, with deep local expertise.
Our people are the key to our success. We're committed to fostering a culture of creativity, belonging and continuous learning, attracting and developing the brightest talent, and providing exciting career opportunities that help our people grow.
For more information, visit WPP.com.
About Data & Technology Solutions
WPP’s Data & Technology Solutions is WPP’s unified global data products and technology team. We work with our agencies and clients to build data-driven solutions and technology product to power marketing transformation.
WPP Open is our AI platform for marketing, it connects marketing professionals, data, tools and AI in a single place. WPP Open is the simplest, safest and fastest way to realise the benefits of scaled AI – delivering better-informed creative ideas faster and at scale.
Why We Are Hiring:
We are seeking a technically minded product leader to define what WPP's agents are actually able to do. This is a new role, created to own the layer beneath the interface: the core set of skills and tools that agents call, the guardrails that keep them safe to use, the data and context they reason over, and the agentification of WPP's own applications so that they can be operated by an agent and not only by a person.
The ideal candidate will have taken an established product and made it agent-native — exposing its capabilities as tools, skills and data an agent can call, defining the contracts, permissions and behaviour around them, and proving the result is reliable to put in front of enterprise customers. Skills, tools and agentification are not new in the industry, and we are looking for someone who has already done this work somewhere it mattered.
This is a more technical product role in the Agentic Experience pillar and sits at the intersection of product and AI. You may come from product management, engineering or data science. What matters is that you can hold a clear point of view on where a capability belongs — in the model, in a tool, in the data, or in the interface — and defend it with evidence.
It is also a visionary / forward-looking role in the pillar. A good deal of what you will own does not exist yet, and part of the job is deciding what should. This requires a product leader who is comfortable with ambiguity but still ships, and who can bring a large organisation along with them.
What You Will Do:
Within this IC role, reporting into the Senior Director Product Enablement WPP Open – you will:
- Own the vision, strategy and roadmap for skills, tools and agentification across WPP Open, ensuring alignment with the broader Open strategy and business objectives.
- Define the core set of skills that WPP's agents are built from — what exists as a first-party skill, what is left to users to compose, and what should not be a skill at all.
- Own the tool layer: how WPP and third-party capabilities are exposed to agents through well-defined interfaces, contracts, permissions and connectivity standards such as MCP.
- Lead the agentification of WPP applications, working with the teams that own them to make their capabilities callable, observable and safe to operate agentically.
- Define the guardrails (what an agent may do, on whose authority, with what data), working with Agent Governance so they are built into the product.
- Own the evaluation and quality approach for skills and for chained agent output: how capability is tested before release and monitored after it.
- Define the data and context strategy that agents reason over, spanning retrieval, grounding, memory, context management and the interfaces to WPP's data and knowledge assets.
- Work closely with Engineering, Design, UX and Data to deliver a coherent skills layer. Set clear objectives with teams and ensure alignment of plans and workstreams to achieve them.
- Provide day-to-day vision, direction and motivation to the cross-functional product team, including product management, data analysts, engineers and product enablement.
- Use data to drive product strategies and plans, gathering quantitative and qualitative feedback from stakeholders and systems to enhance product adoption and usage continually.
- Act as the voice of the customer by balancing platform priorities with the needs of agencies, operations teams and clients, and make an unfamiliar technical area legible to senior stakeholders so that new capabilities are understood and adopted, and their benefits championed.
What You Will Need
- Experience in Product Management, Product Ownership, engineering leadership or applied data science, with significant time spent on AI or platform products.
- Proven track record of taking an established SaaS or enterprise product and making it agent-native.
- Deep and current knowledge of agent architectures: LLMs, tool, skill and function calling, RAG and retrieval design, context & memory management, multi-agent orchestration, and connectivity standards such as MCP.
- Direct experience with working with agent and tooling ecosystems such as MCP/A2A servers and clients, LangChain or LangGraph, Semantic Kernel or comparable skill and tool frameworks.
- Experience defining guardrails, permissions and safety controls for autonomous or semi-autonomous systems and making them part of the product.
- Experience with evaluation of non-deterministic systems: test sets, scoring rubrics, regression testing, human review and production monitoring.
- Understanding of APIs, system integrations, workflow orchestration and data interoperability, with the ability to hold a credible technical conversation with senior engineers.
- Experience with data and knowledge platforms — retrieval, embeddings, semantic search, taxonomy and grounding against enterprise content.
We believe the best work happens when we're together, fostering creativity, collaboration, and connection. That's why we’ve adopted a hybrid approach, with teams in the office around four days a week. If you require accommodations or flexibility, please discuss this with the hiring team during the interview process.
WPP is an equal opportunity employer and considers applicants for all positions without discrimination or regard to particular characteristics. We are committed to fostering a culture of respect in which everyone feels they belong and has the same opportunities to progress in their careers.
Please read our Privacy Notice (https://www.wpp.com/en/careers/wpp-privacy-policy-for-recruitment) for more information on how we process the information you provide.
How we rate this
Senior Product Director, Agentification, Skills and Data at WPP rates 74 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- Walk me through how you've used LangChain in your day-to-day work.
- What are the limits of LangGraph that you've run into, and how did you work around them?
- What's a project where you used Semantic Kernel hands-on?
- Describe a typical day in a role like this one: which parts run through AI directly?
Adapt your resume
- List these exact terms on your resume: RAG, LangChain, LangGraph, and Semantic Kernel. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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