VP, Operations Transformation

The Opportunity 

AI is reshaping how businesses operate — and most companies are still figuring out what that actually means in practice. Merkle is not waiting to find out. We are building a team whose entire purpose is to apply AI to the real, complex problems that sit at the heart of how a large professional services organization runs: how we staff and plan, how we track and improve financial performance, how we deliver for clients, how we grow. 

This role is rare. It sits at the intersection of strategic leadership, AI expertise, and operational depth — and it has the full backing of the COO to make a meaningful difference. You will not be handed a playbook. You will write it. You will decide where AI can have the most impact, build the team and the solutions to get there, and show the business what is possible when operations is run by people who think differently. 

If you are someone who gets energized by hard problems, who wants to lead a team that is doing something genuinely new, and who believes that AI is most powerful when it is connected to a deep understanding of how work actually gets done — this is the role for you. 

What You Will Do 

Think strategically, lead with vision 

• Develop a clear, compelling point of view on how AI should transform operations at Merkle — and bring leadership, stakeholders, and your team along with you 

• Identify the highest-leverage opportunities across finance, staffing, project delivery, and sales operations — and sequence the work in a way that delivers value fast and builds toward something bigger 

• Inspire a distributed team of AI practitioners and analysts to do their best work — not by managing them closely, but by giving them clarity, direction, and a reason to care 

• Be the person in the room who sees around corners — who understands the business well enough to anticipate what will be needed before anyone asks for it 

Understand the problem before building the solution 

• Invest the time to genuinely understand how operations works — the workflows, the pain points, the decisions that get made manually that shouldn't be, the places where the business is flying blind 

• Partner with finance, HR, resource management, and delivery leadership not just to gather requirements, but to build real relationships and real understanding 

• Define the problem clearly before directing the team toward a solution — a well-defined problem is half the answer 

• Balance depth with speed. This is not a role for endless discovery. You know when you have enough to move. 

Lead a team to deliver AI-powered solutions 

• Direct a team of AI-native business analysts, a technical architect, a machine learning engineer, and a data and modeling specialist toward solutions that are actually adopted and used 

• Set clear expectations for output — working solutions, not research decks or prototypes that go nowhere 

• Use tools like Claude and other AI platforms as the foundation for how the team works, not as a novelty 

• Work alongside the technical members of your team to ensure what gets built is scalable and maintainable — not just impressive in a demo 

Drive measurable outcomes 

• Own the results, not just the activity. Every project should have a clear, measurable improvement it is driving toward 

• Report to the COO with honesty and clarity — what is working, what is not, and what comes next 

• Continuously look for opportunities to reduce manual effort, improve decision quality, and increase the speed at which the business can act on information 

Keep what gets built working 

• Oversee a small operational support function whose job is to make sure that solutions, processes, and tools stay current and continue to serve the business once they are live 

• Ensure the business always has somewhere to go when they need help — whether that is a process question, a tool that needs updating, or a new need that has emerged since something was built 

• Build a culture of maintenance and ownership on the team — great work does not end at launch 

• Identify when something that was built is no longer fit for purpose and make the call to update, replace, or retire it 

Who You Are 

• You have 8+ years of experience in operations, AI-driven solution development, or a related leadership role — and you have a track record of delivering, not just advising 

• You have hands-on experience building with LLMs — prompt engineering, agentic workflows, API integration, and AI application architecture. You have shipped AI-powered tools in a production environment, not just explored them in a sandbox 

• You have experience with the full solution lifecycle — from scoping and data requirements through to deployment and iteration. You know what it takes to move from a working prototype to something the business actually relies on 

• You think big. You can articulate a vision for what AI-enabled operations looks like and make people want to be part of building it 

• You are deeply curious about how businesses actually work. You ask good questions, listen well, and do not jump to solutions before you understand the problem 

• You understand AI at a meaningful technical level — how large language models work, how to design workflows that use them effectively, how to evaluate whether something is worth building 

• You have led distributed or offshore teams and know how to create alignment and momentum across time zones 

• You balance strategic thinking with a genuine bias toward delivery. Research without output is not something you tolerate in yourself or your team 

• You communicate clearly and credibly at every level — from a working session with an engineer to a progress update with a COO. You write and speak with precision, and people leave your conversations knowing exactly what you said and what happens next 

• You are a skilled executive communicator. You have presented to senior leadership — including C-suite and cross-functional executives — and you know how to tell the story that gets the room bought in. You can take complex operational or technical work and frame it in a way that makes the business case clear, earns the investment, and builds confidence in delivery. Within Merkle and across dentsu, you will be the face of this team’s work

• You are comfortable with ambiguity. This is a role where the path is not fully defined, and you will need to help define it 

Nice to Have 

• Background in digital marketing, agency operations, or professional services 

• Experience working within a large, matrixed organization 

• Familiarity with financial planning, resource management, or project delivery tooling 

• Machine learning or data engineering experience 

• Experience with Python, SQL, or equivalent — you do not need to be a full-stack engineer but you can read code, debug a workflow, and have a credible conversation with a technical team member 

• Familiarity with AI governance, data privacy considerations, or responsible AI practices 

Dentsu is committed to providing equal employment opportunities to all applicants and employees. We do this without regard to race, color, national origin, sex , sexual orientation, gender identity, age, pregnancy, childbirth or related medical conditions, ancestry, physical or mental disability, marital status, political affiliation, religious practices and observances, citizenship status, genetic information, veteran status, or any other basis protected under applicable federal, state, or local law. 

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