Job description

About CoLab At CoLab, we help mechanical engineering teams bring life-changing products to market years sooner. We build AI for engineers designing cars, medical devices, and jet engines. Products this complex aren't sketched and sent to production. Teams spend months on iterations, reviews, and tests, predicting how every part performs before anything is built. CoLab is where those reviews happen, and we capture the rationale behind every change. Other tools show what changed between versions. Only CoLab knows why. That's how our AI helps manufacturers like Bobcat, Triumph Motorcycles, and GE Appliances make better decisions, eliminate rework cycles, and get to market faster. Proudly based in St. John’s, Newfoundland, CoLab started with one customer in 2018. Since then we’ve raised a $72M Series C , been named the 57th fastest growing company in North America by Deloitte ( Fast 500™ ), signed multi-year AI partnerships with companies like Bombardier , and grown to a team of 250+. About the Role This is a high-impact role that helps define how CoLab delivers technical value to its most strategic customers. You'll act as a dedicated technical problem-solver and trusted advisor, embedding with enterprise customers to optimize how they use CoLab—especially our AI tools. You'll help large mechanical engineering orgs rethink how they manage feedback, data, and decision-making across design and PLM. That means getting deep into customer workflows, testing new ways of working, and building repeatable methods the rest of the team can scale. You'll work within our forward deployed team, alongside a technical program manager, software FDE, and customer-facing teams to close technical gaps, shape product direction, and directly influence customer success. This role isn't about selling or pitching—it's about deeply understanding engineering problems and solving them alongside the customer. Our Ideal Candidate You're a mechanical engineer by trade but your superpower is applying that knowledge in creative, systems-level ways. You're curious, technical, and comfortable working through ambiguity. You've likely been a design engineer or worked in a PLM-heavy environment. Maybe you've dabbled in automation, scripting, or app development for internal tools. You don't need to be the loudest voice in the room—but you can run a sprint, lead a cross-functional project, and talk shop with both customer engineers and internal developers. If the average person might find this job too undefined or complex, that probably excites you. Job Responsibilities Embed with enterprise customers to optimize CoLab usage, with a focus on AI tools like AutoReview and Operator. Investigate and solve complex engineering data and integration challenges across PLM, ERP, QMS, and traditional design feedback tools. Partner with a cross functional team to test and implement new CoLab workflows inside customer environments Collaborate with product teams to identify feature gaps, improve capabilities, and refine AutoReview Build technical documentation, playbooks, and repeatable frameworks based on successful projects Provide mechanical engineering expertise to validate AI-generated results and ensure engineering rigor Qualifications Must-haves: Background in mechanical design engineering, ideally in a medium to large sized organization. Strong understanding of PLM systems and enterprise engineering data architecture Demonstrated ability to lead technical projects and cross-functional collaborations Experience working directly with customers or internal stakeholders to solve technical problems Comfort working in fast-changing, ambiguous environments Strong written communication and documentation skills Working knowledge of high level AI architecture, specifically LLMs. Familiarity with APIs, data integrations, and enterprise architecture concepts Nice-to-haves: Experience with internal tool development, scripting, or automation Exposure to AI/ML tools applied to engineering workflows Prior work in design consulting or product development at scale Extra Details This is a full-time, permanent position with a competitive compensation package that includes stock options Unlimited paid vacation, extended health benefits, and RRSP/401k matching Remote-friendly within Eastern or Central time zones in Canada or the US. This role will have a travel component to visit customers onsite. Customer visits are typically 1-3 days total, one or two a month. Equity Note Frequently cited statistics show that people who identify with historically marginalized groups are likely to apply to jobs only if they meet 100% of the qualifications. We encourage you to help us break that statistic and apply even if you don't meet every single qualification—your potential is what matters most to us.

Requirements

Must-haves

Our Ideal Candidate
You don't need to be the loudest voice in the room—but you can run a sprint, lead a cross-functional project, and talk shop with both customer engineers and internal developers.
If the average person might find this job too undefined or complex, that probably excites you.
Embed with enterprise customers to optimize CoLab usage, with a focus on AI tools like AutoReview and Operator.
Investigate and solve complex engineering data and integration challenges across PLM, ERP, QMS, and traditional design feedback tools.
Partner with a cross functional team to test and implement new CoLab workflows inside customer environments
Collaborate with product teams to identify feature gaps, improve capabilities, and refine AutoReview
Build technical documentation, playbooks, and repeatable frameworks based on successful projects
Provide mechanical engineering expertise to validate AI-generated results and ensure engineering rigor
Background in mechanical design engineering, ideally in a medium to large sized organization.
Strong understanding of PLM systems and enterprise engineering data architecture
Demonstrated ability to lead technical projects and cross-functional collaborations
Experience working directly with customers or internal stakeholders to solve technical problems
Comfort working in fast-changing, ambiguous environments
Strong written communication and documentation skills
Working knowledge of high level AI architecture, specifically LLMs.
Familiarity with APIs, data integrations, and enterprise architecture concepts

Nice-to-haves

Experience with internal tool development, scripting, or automation
Exposure to AI/ML tools applied to engineering workflows
Prior work in design consulting or product development at scale
Extra Details
Remote-friendly within Eastern or Central time zones in Canada or the US.
This role will have a travel component to visit customers onsite. Customer visits are typically 1-3 days total, one or two a month.

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Keywords to mirror

airestml

Platform: greenhouse
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Benefits

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