Senior Product Manager, AI Platform

• With 20+ years experience of serving the industry through its digital transformation, we're stable, profitable, and have developed a loyal customer base (that continues to grow).
• We build software for summer camps, an industry that enables meaningful experiences for kids.
• We work on interesting, ambitious projects that create real value for our clients.
• We know our team members feel their work has an impact on the organization's purpose.
• At the same time, we are genuinely committed to work/life balance. Our team members feel they have the flexibility to take time off when needed and feel supported in making use of flexible working arrangements.
• We invest in emerging technology and cutting-edge leadership and are proud to take an "AI-Enabled" approach in our solutions.
• We've been listed on Outside Magazine's 50 Best Places to Work for 8 consecutive years for our values-led culture and employee experience.

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.

• 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.

• 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.

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.

We're actively taking steps to make sure our culture is inclusive and that our processes and practices promote equity for all, including people of color, people from working-class backgrounds, women, and members of the LGBTQ+ community. We welcome and encourage applications from people with these identities or members of other historically marginalized groups.

Research shows that women and people of color tend not to apply to jobs unless they believe they are 100% qualified and apply to fewer senior-level positions. With that in mind, we encourage you to apply if you're not sure whether you meet our qualifications. We'd love to have the opportunity to consider you!

We encourage applications from parents, parents-to-be, and those responsible for the caretaking of others. We offer paid parental leave for birthing and non-birthing parents (including for adoption, surrogacy, and foster care placement) and paid loss leave to recover from miscarriage or stillbirth. The company's HSA and wellness allowance contributions may be used toward childcare, eldercare, adoption fees, and fertility treatments like IVF, among other expenses.