Senior Product Manager

About Ampliwork, Inc

Ampliwork builds Enterprise-Grade AI Agents that amplify Human Potential™ to drive

business productivity and growth since 2017. Ampliwork’s

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.

The Mission

You will be the single point of accountability for two to four client engagements at a time. A typical engagement looks like this:

Scope the problem with the client in a working session. Diagnose what they actually need, not what they asked for.

1. Write the proposal. Pitch it. Close the next phase.

1. Build the first working prototype yourself, often inside the first week.

1. Run the project. Own the plan, the timeline, the milestones, the risks, and the status. Keep clients and internal stakeholders in the loop without anyone having to ask.

1. Bring in our engineers when the project graduates from prototype to production. Lead them. Stay accountable for delivery.

1. Run workshops, demos, and iteration sessions with the client. Keep the loop tight.

1. Hand off or maintain, depending on the engagement shape.

You'll do design work, project management, and a meaningful amount of coding. You won't be writing the production backend yourself, but you'll prototype enough that the engineers know exactly what to build.

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're the person colleagues come to when they want to get more out of AI, and you actively raise the floor for everyone around you by sharing prompts, workflows, and shortcuts.
• Extremely organized. You can hold four engagements 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.

• High social energy and sharp judgment. You get fuel, not fatigue, from people. You read a room quickly. You know when to push, when to listen, when to lighten things up, and when to hold the line. Clients and colleagues both want you on their projects.

• Excellent communicator. Clear writer, confident speaker. You build decks that move people from "interesting" to "yes." PowerPoint, Keynote, Slides, you know how to make a presentation land. You take this part of the craft seriously.

• Creative problem solver. You see two ways to solve a problem when most people see one. Ambiguous, messy problems energize you. You'd rather start from a blank page than a finished spec, and what you make is well-designed, not just functional.

• Can sell. Not in a slick way. You listen for the real need, frame a solution that fits, and ask for the close. You can run a scoping call, lead a workshop, and pitch a proposal that gets a yes.

• Can prototype. You have an engineering foundation and can still build. You can turn an idea into a working prototype in days using code, APIs, LLMs, and modern AI tools. You may not want to spend your days writing production backend code anymore, but you've done it before and you know what good engineering looks like.

• Stretched, not scared. The breadth of this role energizes you. You want the whole arc, not a slice of it.

What we're looking for

• Engineering foundation. You started your career building software and are still technical enough to prototype, debug, read code, and work deeply with engineers.
• Moved from engineering into product. You discovered that you're strongest at figuring out what should be built and why — talking to users, shaping ambiguous problems, making tradeoffs, and driving a solution from idea to production.
• Still a builder. You don't need an engineering team to test an idea. You can turn a rough problem into a working prototype yourself using code, APIs, LLMs, and modern AI development tools.
• Product judgment. You can take a messy customer request, find the underlying problem, decide what matters, and design the simplest solution that creates real value.
• Strong with customers. You're comfortable running a technical discovery session, challenging assumptions, presenting to executives, and earning trust with both technical and non-technical stakeholders.
• End-to-end ownership. You're happiest owning the whole arc: discovery, solution design, prototype, proposal, delivery, iteration, and outcome.
• AI-native. You build with LLMs and agents constantly and have strong opinions about what works, what doesn't, and where the technology is going.
• Systems thinker. You think in workflows, architectures, constraints, and outcomes rather than isolated features.

The backgrounds we're most interested in:
Software engineer → product manager / product lead; founding engineer → founder/product; technical product manager with a real engineering background; or a similar path where you built software first and moved closer to customers and product over time.

Nice-to-haves

• Shipped LLM-powered products or agentic workflows to production
• Experience in B2B enterprise software
• Design fluency (Figma, prototyping in code, strong taste for interfaces)
• A side project, GitHub presence, or other evidence that you still build