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You will identify complex operational problems and prototype AI-driven solutions to integrate into scalable production systems. Additionally, you will lead the development of decision engines and attribution capabilities while collaborating closely with engineering teams.
Join a small, hands-on product team at an AI-focused marketing services company working to redesign core operations around an owned AI platform. You will identify high-impact problems, prototype solutions, and partner with engineering to bring reliable systems into production.
Identify complex operational problems, define measurable outcomes, and prototype AI-driven solutions using real data.
Work closely with engineers to turn validated prototypes into reliable, scalable production systems.
Develop ways to measure and address challenges such as content decay.
Lead development of a decision engine tailored to different user needs.
Guide closed-loop attribution capabilities that connect client actions to revenue.
Shape a platform that balances shared capabilities with the needs of different client types and industries.
Engage directly with users and data, and communicate product decisions clearly and concisely.
Two to eleven years of relevant experience building products or technology solutions.
Experience building and shipping functional prototypes with AI coding tools and real-world data.
Knowledge of AI capabilities, limitations, failure modes, and edge cases, with experience designing systems for production.
Strong systems thinking, including an ability to assess downstream effects, operational impact, and when to generalize a solution.
Experience defining measurable operational problems and validating outcomes with data.
Ability to partner closely with engineering and write clear, concise documentation.
Background in marketing services or experience building decision engines, reporting tools, or attribution systems is relevant.
Salary range: $160,000 to $230,000 USD annually. Visa sponsorship is not available.
Remote within the United States.
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