Ideal start timeline: September 2026

Role status: Exempt

Compensation: Our target hiring range is $180,000 - $220,000 plus participation in our Annual Bonus Program with eligibility for $12,000 bonus. Actual compensation will be commensurate with experience and skills.

Campminder's Flexible Working Location:Our employees have the option to work 100% remotely within the United States or their choice of days at home and at our office in Boulder, Colorado. We host a variety of all-company hybrid meetings and social events. We require anybody working remotely to have a very reliable, high-speed internet connection.

This role's mission & overview:

Campminder is building an AI layer beneath every product we make, grounded on 25 years of camp data across close to 1,700 camps and a RAG system that's live today. This role builds that shared foundation, the retrieval, evaluation, services, and patterns every product team builds on, and works across those teams to turn it into AI capabilities camp leaders actually use. The hard part isn't producing a demo. It's designing infrastructure many teams can build on, defining how its quality is measured, and getting it adopted in the wild. It's not a role for adding an AI feature so a product looks current. It's for someone who sees the whole system, finds the seam that matters, and makes the complexity smaller for everyone downstream.

As a Senior Product Manager of AI Platform on our Product team, you will:

• Build and own the shared AI infrastructure our products stand on: retrieval and grounding on camp data (the RAG system is live, extend it), evaluation and observability, and the services and patterns every team reuses instead of rebuilding.
• Work across product teams to turn that foundation into capabilities in the wild. Shape how it lands in each product, keep teams unblocked, and drive real adoption. This cross-functional work is most of the job.
• Own how quality and trust are measured across the platform, precisely enough to catch a regression before a customer does, with a person in the loop where the stakes are highest.
• Lead the lifecycle of LLM and ML work streams with your AI and data engineering partners, and make deliberate build vs. buy and train vs. fine-tune vs. ground-with-RAG calls without chasing hype.
• Prototype hands-on to explore and de-risk direction, and expect to throw a healthy share of it away. It's one tool for finding the right thing to build, not the whole job.
• Grow the internal-automation side as the foundation matures, and write down what you and your partners learn so the next team starts ahead.

We think a successful candidate will bring:

• Systems thinking, pattern recognition, and a bias to simplify. You see how the whole thing fits, spot the pattern that repeats, and reach for the simplest design that works. This is the core.
• AI product depth. You've productized AI before, not just added an AI feature. You reason well about when to train or fine-tune versus ground with retrieval, you know RAG and evaluation in practice, and you hold your own with AI engineers on models, agents, and trade-offs. This role builds the AI infrastructure itself, so this depth is required, not a bonus. You prototype hands-on to de-risk direction, and you don't need to own the MLOps infrastructure yourself.
• A platform and infrastructure mindset. You've built foundations other teams build on, you treat those teams as your customers, and you keep them unblocked without building everything they ask for.
• Cross-functional influence. You get things adopted across teams you don't own, earning trust and driving real usage rather than shipping and hoping. This is where most of the value lands.
• A track record of shipping through the full loop, from idea to working build to production to iterated. You can point to what you built, what got used, and what you changed. Talking about iteration isn't the same as living it, and we'll know the difference.
• An eval instinct. You ask "how would we know this is good?" before "how do we build it?", and you can define quality precisely enough to measure and defend it.
• Coachability. You get sharper when someone pushes back, not defensive, and you often set the pace rather than slow it.

Our Interview Process:

1. 45 min - interview with People & Culture
2. 60 min - interview with Hiring Manager
3. Take-home assignment on your own time: a real Campminder AI problem. We're looking at how you define "good," how you'd evaluate it, and how you reason about a system that won't behave the same way twice.
4. 60 min - present and defend your assignment to a technical and product panel. Expect pushback. How you handle it matters as much as the answer.

A few of the benefits we are proud to offer:

• Robust medical, dental, and vision coverage options with generous employer contributions, plus a $500 employer HSA contribution for HSA-compatible plans
• Ability to choose where you work - remotely, in the office, or a mix!
• A variety of resources to support mental health and emotional well-being
• 12 weeks of 100% paid parental leave for all new parents, including via adoption, surrogacy, and foster care
• 401(k) with 4% company matching
• Trust-Based (flexible) PTO (and yes, we use it!)
• $900/year wellness allowance
• Company-paid subscriptions, training, and support for using AI professionally and personally. We have a team dedicated to enabling our AI capabilities for our team members and our customers!