Junior Product Manager

About Ampliwork, Inc

Most of the market is selling AI tools. We're shipping AI colleagues.

Ampliwork builds production-ready AI agents that own specific jobs inside enterprise operations teams. They execute workflow steps, handle handoffs, escalate exceptions, and run with the accuracy, continuous learning, and full visibility that highly regulated industries demand. We work across Tax, Financial Services, and Transportation. We don't deliver capabilities. We deliver outcomes, backed by SLAs.

Our vision is to give every enterprise operations team a digital workforce. Not a copilot. Not a chatbot. A team of AI agents that show up, do the job, and free human ops people to spend their time on work that actually requires them.

That unlocks three things for our customers:

1. Lower operational cost. Real reductions, not slideware promises.

1. Scale without headcount. Volume goes up. The team doesn't have to.

1. Speed. Workflows that took days finish in minutes.

We've been at this since 2017. We're now a 25-person team with offices in Montreal, Boston, and London (UK). Our development team is based in Montreal, which is where this role sits. We're growing fast into one of the most consequential bets in enterprise AI: replacing operational labor at scale, in the hardest regulated environments, with software that delivers measurable results.

If you want to work on AI that real companies deploy and depend on, not demos, this is the place.

A few things that matter to us:

• We ship software enterprise clients actually use in production. No demoware.

• We have opinions about craft. Speed and quality are not a tradeoff if you're good.

• We use AI at every hour of the day. Claude, Cursor, modern agent frameworks. If you're not already living inside these tools, this isn't the role for you.

About the role

You'll support two to four client engagements at a time, working closely with the senior lead on each one. Your job is to move the work forward: build, organize, communicate, and follow through. A typical week looks like this:

1. Build. Turn scoping notes and requirements into working prototypes, often inside a few days, using modern AI tools.
2. Run the day to day. Own the project logistics: timelines, task lists, meeting notes, action items, and status updates. Nothing slips.

1. Prepare materials. Draft the decks, one-pagers, and demo scripts. Make them clear and make them land.

1. Show up in the room. Join scoping calls, workshops, and demos. Take great notes, capture follow-ups, and close the loop with clients and engineers.

1. Support delivery. Work with our engineers as prototypes graduate to production, translating what the client needs into clear, buildable detail.

1. Keep quality high. Test the product, catch what's broken, and iterate until it's better than expected.

You'll do prototyping, project coordination, and presentation work, learning the full arc of an engagement under a senior lead. Over time, you'll take on more ownership.

What you'll do

• AI-native. You don't use AI. You think in it. Claude, Cursor, and modern agent frameworks are how you reason, build, write, and solve problems, not tools you visit on occasion. You share prompts, workflows, and shortcuts, and you make everyone around you faster.

• Extremely organized. You can hold several projects in your head at once and nothing slips. Calendar, notes, follow-ups, deliverables. People who work with you feel calmer because of it.

• Strong bias for action. You don't wait to be told. You see what needs doing and start. You'd rather ship something rough today and refine it tomorrow than perfect it in your head for two weeks.

• Can prototype. You build working things in days using modern AI tools, even if you're not yet a production-grade engineer.

• Good communicator. Clear writer, confident speaker. You can build a clean deck, write a crisp update, and make a point without burying it.

• Eager to grow. You want to learn how the whole thing works, take feedback well, and level up fast. You're hungry for the next level of responsibility.

• Reliable and thorough. Details are the job. You follow through, double-check your work, and don't need to be reminded twice.

What we're looking for

• Some experience building with LLMs, whether at work, in school, or on side projects

• Design fluency (Figma, prototyping in code, taste for interfaces)

• A side project, a GitHub presence, or a blog where you've thought out loud about something

• An internship or early role in product, consulting, or a startup the experience and attributes of the ideal candidate