Forward Deployed Growth Strategist (Commercial AI Solutions)

About You

Did you start your career in Media, Sales, or Analytics? Have you lived the day-to-day—a Monday spent reconciling three data sources, the analysis you rebuilt by hand every month, the question you knew was answerable if only you had a week to dig?

Then you know the challenges of this work—the real version you worked around every day.

At some point, you hit a wall. You knew exactly what needed to exist, but you were stuck waiting on someone else’s roadmap. So you built it—and then you kept building to drive growth.

Today, you design and ship AI systems: agents that run reliably against messy, real-world data; pipelines that hold up under load; and tools people depend on every day. You have production scars. You own the full lifecycle—architecture, build, evaluation, and deployment—and you know what it takes to keep a system running once people rely on it.

But you never stopped thinking like an operator. You know the difference between an interesting technical problem and a real commercial one. You are equally credible with a finance leader and a staff engineer, changing vocabulary without changing substance.

You are half commercial, half technical—with no discount on either side. Not a business leader enthusiastic about AI, and not an engineer learning the business. The work you are most proud of is not a model or a demo. It is a system people depend on—or a number that moved because of something you built to drive growth

About the Role

We are building this capability across every part of our commercial organization: Media. Sales. Strategy. Analytics. Each team is sitting on opportunities to make decisions faster, sharper, and at a scale no spreadsheet will ever reach.

You will embed with a team running a real piece of a $6B+ business, across 41 categories identify where AI can materially change how it operates, and build the systems that make it happen. From problem definition through architecture, deployment, and adoption—it is yours to own. Then you drive adoption with the operators who own the P&L, improving what you built and pushing until the number actually moves.

You are not advising from the sidelines or feeding tickets into someone else’s backlog. You are working directly with operators to eliminate manual work, surface decisions sooner, and create measurable commercial impact, while driving growth.

What You'll Do

• Embed with a team. Operate as a member of the commercial team you support. Learn their rhythm, the metrics their leaders are held to, and the decisions they make every week to grow the business.
• Diagnose before you build. Find the revenue and margin opportunities worth pursuing, and prove the case in the data before writing code.
• Build agentic solutions end to end. Design and ship AI agents, LLM pipelines, data products, and internal tools that plug into live commercial workflows and take real action. You own architecture, build, evaluation, and production.
• Master our enterprise data platform. Develop deep fluency in the platform underpinning our AI roadmap—data pipelines, data modeling, and the application layer—and use it to scale what you build beyond a single team. Prior experience with it is not required; the ability to get productive fast is.
• Keep it running. Own reliability, evals, observability, and cost. A system nobody trusts is a system nobody uses.
• Own the outcome. Deploy alongside the operators who own the P&L, drive genuine adoption, and measure success by the number that moved—not by the system that launched.
• Translate in both directions. Write the prompt and the code, then explain the margin impact to a finance lead and the workflow change to a category manager.
• Prioritize with leadership. Work directly with senior commercial leaders to decide where AI creates the most value, and say no to the rest.
• Build the capability, not just the tool. Document and hand off so one-off wins become repeatable systems—and reuse what your counterparts across the organization have already built.

What You'll Bring

• 5–7 years of experience spanning both sides of this role—time on a commercial team where you were accountable for a business result, and hands-on time building software.
• Deep expertise in at least one commercial discipline. Sales, media, strategy, analytics, or an adjacent commercial function. Knowing one of them cold matters far more than knowing a little about all of them.
• Proven commercial impact. You have led revenue growth or margin expansion somewhere real, and can explain exactly what you moved and how.
• Commercial data literacy. Comfort with the data of your discipline—sales, media spend, margin, funnel, inventory, marketplace—and the judgment to know which number matters and which is noise.
• Production AI engineering. You have designed, built, and shipped agentic systems that run in production—multi-step agents, tool use and orchestration, retrieval, structured outputs, evaluation, and human-in-the-loop design—with real users and real consequences when they fail. Be ready to walk through the architecture and what you would change.
• Real technical range. Strong Python, SQL, and API fluency; comfort with cloud data warehouses and modern data modeling; enough front-end capability to build a tool people will actually open. You write code that someone else can maintain.
• Credibility and speed. You earn trust from analysts to executives, operate well in ambiguity, and move without waiting to be told how.