About the role
About Us
We're a Montréal-based AI engineering practice working on-site and remote, in French and English. Most firms staff a team and send a deck. We place one engineer inside a client's business who carries the project end to end: scoping, building, shipping, adoption.
We find where time is lost and where value is left on the table, ship a first build fast, and iterate on real feedback. Once a system ships, we stay to operate it - updates, security, model changes - so it stays dependable as the client grows. Everything we build is designed to run two ways: a clean interface people drive today, and the same controls an AI agent can run as agents become dependable. We build on what clients already have, no rip-and-replace, and we measure success in outcomes, not features shipped.
The role
As a Forward Deployed Engineer, you're embedded inside a client's business and own the outcome. You sit with their team, learn how the work actually flows, and turn that into working software they adopt.
Day to day, you'll: Scope problems directly with client stakeholders and translate real workflows into technical requirements Design system architecture and build the back-end services, APIs, and integrations that fit into what the client already runs Ship small, real builds quickly and iterate on how people actually use them Deploy, monitor, and maintain systems in production, owning reliability and security Document your work thoroughly so systems run as products, not one-off projects Work across French and English as the client needs
This isn't a heads-down backend role. You're on the client's floor, accountable for something that has to work and keep working.
What we're looking for
You build software that ships and holds up in production - clean, tested, maintainable code, and the judgment to know when it's good enough Solid back-end fundamentals: APIs, databases, and integrating with systems you didn't build Experience running software in production - cloud, CI/CD, monitoring, and security aren't new to you You work well with non-technical people: you listen, ask the right questions, and turn business needs into something real You're self-directed and accountable - you own outcomes and maintain what you ship, rather than handing it off Comfortable in a bilingual French/English setting; fluent in at least one, willing to work in both Experience with AI, ML, or data-driven systems is a plus, not a requirement - we care more that you can learn fast and build Formal CS background, self-taught, or somewhere in between - if you can do the work, we want to hear from you
About bluecap
We're a Montréal-based AI engineering practice working on-site and remote, in French and English.
Most firms staff a team and send a deck. We place one engineer inside your business who carries the project end to end: scoping, building, shipping, adoption. One person, accountable for the outcome, backed by a team and documented systems so the work is never a single point of failure.
Your embedded engineer meets your people and teams, finds where time is lost and where value is left on the table, and identifies the use cases worth pursuing. The first build is chosen together: small enough to ship fast, real enough to matter, usually underway by week three. Progress shows up as working software your team can try early and steer. And once a system ships, we stay to operate it, handling updates, security, and model changes so your tools stay dependable as your business evolves.
Every system we build is designed to run two ways. Today your team drives it through a clean, familiar interface. Underneath sit the same controls an AI agent can operate, so as agents become dependable, they run the system your team already trusts. Nothing gets rebuilt.
The principles are simple. Adoption is the product: success is measured in outcomes, not features shipped. We build on what you already have, with no rip-and-replace. And we finish what we build: systems run as products, monitored and maintained, measured by whether they keep running, not whether they launched.
Similar Jobs
About the role
About Us
We're a Montréal-based AI engineering practice working on-site and remote, in French and English. Most firms staff a team and send a deck. We place one engineer inside a client's business who carries the project end to end: scoping, building, shipping, adoption.
We find where time is lost and where value is left on the table, ship a first build fast, and iterate on real feedback. Once a system ships, we stay to operate it - updates, security, model changes - so it stays dependable as the client grows. Everything we build is designed to run two ways: a clean interface people drive today, and the same controls an AI agent can run as agents become dependable. We build on what clients already have, no rip-and-replace, and we measure success in outcomes, not features shipped.
The role
As a Forward Deployed Engineer, you're embedded inside a client's business and own the outcome. You sit with their team, learn how the work actually flows, and turn that into working software they adopt.
Day to day, you'll: Scope problems directly with client stakeholders and translate real workflows into technical requirements Design system architecture and build the back-end services, APIs, and integrations that fit into what the client already runs Ship small, real builds quickly and iterate on how people actually use them Deploy, monitor, and maintain systems in production, owning reliability and security Document your work thoroughly so systems run as products, not one-off projects Work across French and English as the client needs
This isn't a heads-down backend role. You're on the client's floor, accountable for something that has to work and keep working.
What we're looking for
You build software that ships and holds up in production - clean, tested, maintainable code, and the judgment to know when it's good enough Solid back-end fundamentals: APIs, databases, and integrating with systems you didn't build Experience running software in production - cloud, CI/CD, monitoring, and security aren't new to you You work well with non-technical people: you listen, ask the right questions, and turn business needs into something real You're self-directed and accountable - you own outcomes and maintain what you ship, rather than handing it off Comfortable in a bilingual French/English setting; fluent in at least one, willing to work in both Experience with AI, ML, or data-driven systems is a plus, not a requirement - we care more that you can learn fast and build Formal CS background, self-taught, or somewhere in between - if you can do the work, we want to hear from you
About bluecap
We're a Montréal-based AI engineering practice working on-site and remote, in French and English.
Most firms staff a team and send a deck. We place one engineer inside your business who carries the project end to end: scoping, building, shipping, adoption. One person, accountable for the outcome, backed by a team and documented systems so the work is never a single point of failure.
Your embedded engineer meets your people and teams, finds where time is lost and where value is left on the table, and identifies the use cases worth pursuing. The first build is chosen together: small enough to ship fast, real enough to matter, usually underway by week three. Progress shows up as working software your team can try early and steer. And once a system ships, we stay to operate it, handling updates, security, and model changes so your tools stay dependable as your business evolves.
Every system we build is designed to run two ways. Today your team drives it through a clean, familiar interface. Underneath sit the same controls an AI agent can operate, so as agents become dependable, they run the system your team already trusts. Nothing gets rebuilt.
The principles are simple. Adoption is the product: success is measured in outcomes, not features shipped. We build on what you already have, with no rip-and-replace. And we finish what we build: systems run as products, monitored and maintained, measured by whether they keep running, not whether they launched.