Senior Product Manager, Applied AI

Engine is an AI-native platform for intelligent travel. The company is seeking a Senior Product Manager, Applied AI, to embed within business functions, identify inefficient manual workflows, and deliver AI-powered automation. The role partners with engineering and functional leaders to define metrics, ship and roll out solutions, and transition ownership to the business.

Responsibilities:

• Map the work: Shadow the people doing the work and map each step, handoff and wait, so you know where the time goes
• Pick the workload: Take on one workload at a time, starting with the steps that are repetitive, high-volume and the most time-consuming. You and the functional leader decide what goes next, and you say no to the rest
• Lock the metric: Before anything gets built, get the functional leader to sign off on a cycle time or unit metric, and measure the baseline
• Build and ship: Work with engineering to design and ship automation that replaces manual work at Engine's scale, which includes hundreds of thousands of support cases. Use AI tools and agents to speed up your own analysis, prototyping and documentation
• Scope and roll out: Define the first version you can ship, who uses it first and how it reaches the rest of the function
• Hand it off: Define what it looks like for the function to run the workload without you, with a named owner inside the function
• Make the kill call: If the metric doesn't move, come back with a fix or a decision to stop, with a deadline

Requirements:

• 4+ years in product management, ideally on internal tools, operations or workflow products, with at least one AI or automation product in production
• You've mapped a messy business process, found the steps that cost the most time and removed them
• You're happy spending your first weeks shadowing support agents or accountants, and you judge success by whether the work got faster
• You can baseline a cycle time, define a metric a business leader will sign off on, and account for the costs, including model spend and engineering time
• You understand what LLMs and agents do well, where they fail, and how evals and human review fit into a workflow
• You earn trust with leaders who don't report to you, and you hold the line on scope when everyone wants something different