Responsibilities

• 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.

Requirements

• 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.

Benefits

• The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, flexible spending accounts, health savings accounts (HSA) with company contribution, 401(k) retirement plan with matching, employee stock purchase program, life insurance, AD&D, short-term disability insurance, long-term disability insurance, generous paid time off, company holidays, parental leave, identity theft protection, pet insurance, pre-paid legal insurance, back-up child and eldercare days, product discounts, referral bonus program, and more.