Kettle
Senior Product Manager, AI
Remote - US · Senior
Sponsorship not specified$120k-$150kDetected 11 days ago
ReactLLMsA/B TestingProduct ManagementAgileCadenceCommunication
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odds of building a lasting career here
54Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role80
Entry-level history0
PERM / green-card track0
Lottery odds (Level III)83
Fits your clock70
Sponsors, but it's cap-subject — you still face the weighted lottery (~45% per draw at Level III). Good if you win; have a cap-exempt backup on your list.
Lottery odds assume a STEM candidate.
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About the role
- Our work lives at the intersection of product thinking and brand storytelling; products that are just as considered in feeling as they are in function.
- You'll work on a cross-functional team of creative technologists and product designers, working on the tools, workflows, and accelerators that expand what Kettle and our clients can make.
Requirements
- Experience in product management in an agency, startup, or product environment, with a track record of contributing to AI-powered features, tools, or workflow systems
Nice to have
- Experience contributing to AI-focused client conversations or discovery work, helping translate emerging capabilities into something a client team can understand and react to
- You are able to articulate a clear path forward in an ambiguous space, turning an open-ended brief or emerging capability into a defined workstream with clear priorities and next steps
- Get hands-on with prototyping and experimentation, contributing to the work itself rather than just coordinating it
- Adapt across engagement types, from rapid internal experiments to more structured client delivery
- We'd like to know that you can:
- The target range of base compensation for this role is $120,000-$150,000.
Compensation
- The target range of base compensation for this role is $120,000–$150,000.
Company info
- We are looking for a Senior Product Manager, AI to join our Product team.
This listing is sourced directly from Kettle's careers page and normalized into a canonical job model.