Applied AI Engineer

Location:
Remote within Canada. Quebec is preferred. You must be eligible to work in Canada. The working language is English. Compensation: Salary and equity, discussed based on your experience and the expertise you bring to the team. FlowLinker helps manufacturing companies turn customer requirements into defined solutions that sales and engineering can confidently quote and deliver. The information needed to make those decisions is often scattered across calls, emails, technical documents, product catalogs, and internal knowledge. FlowLinker brings that context together to identify requirements, surface missing information, assess solution fit, and support quoting and delivery handoff. FlowLinker is backed by Antler Canada. You will join an existing engineering team with strong AI expertise and take ownership of specific AI capabilities within a product already in production. You will work closely with the CTO and fellow engineers to shape, build, and improve the parts of the platform you own. What you will work on You will own defined product areas and AI capabilities, with priorities established alongside the CTO and engineering team. Depending on your area of ownership, your work will include:
• Building decision workflows involving entity extraction, requirement classification, product matching, policy checks, and reasoning across structured and unstructured sources.
• Turning validated solutions into structured inputs for quoting, including what is included, what remains unresolved, and what the team can price with confidence.
• Building evaluations that measure accuracy, consistency, hallucination risk, and knowledge drift, and using the results to guide what we ship.
• Designing pipelines for meeting transcripts, technical documents,



product catalogs, customer requirements, and company knowledge.
• Improving the latency, reliability, observability, scalability, security, and cost of the capabilities you own, in collaboration with the engineering team. For the capabilities you own, you will drive technical design, implementation, evaluation, deployment, and ongoing improvement. You will make implementation decisions within agreed architectural standards and collaborate with the team on changes that affect shared systems, infrastructure, or other product areas. What we are looking for
• Experience shipping AI or machine learning systems, with a clear understanding of what you personally designed and what you learned after they reached production.
• Robust Node.js, TypeScript, and software engineering fundamentals.
• Practical experience with LLM APIs, retrieval, embeddings, structured outputs, tool use, and evaluation.
• A clear sense of where a probabilistic model is trustworthy and where the system needs a schema, a rule, or a person.
• Comfort working across experimentation, backend engineering, data pipelines, and production delivery.
• High ownership, sound technical judgment, and the ability to move work forward independently while collaborating closely with other engineers. We care about the systems you have built and the judgment you bring.



Background in knowledge graphs, ontology design, search, agent workflows, industrial automation, manufacturing, robotics, or technical sales will help you get up to speed. What matters most The system has to reach the right interpretation, apply the right technical and organizational context, identify what is still unknown, and produce output a team can trace and defend inside a live customer workflow. We want the simplest architecture that meets that bar. You should be willing to challenge our assumptions when a simpler or stricter design is the one that will hold up. How we work This is a demanding role with consistently long

working hours
beyond a standard 40 hour week. Evening and weekend work should be expected, particularly around releases, customer deployments, and major technical milestones. This level of commitment is an ongoing expectation of the role. We are looking for someone who understands that commitment and actively wants the pace, ownership, and responsibility of building an early stage company. You will have meaningful autonomy over the capabilities you own and a direct voice in technical discussions across the team. Architecture, shared infrastructure, engineering standards, and the AI roadmap are shaped collaboratively with the CTO and fellow engineers. The team has more than $5 million in cloud, model, and developer tool credits. We use that room to test frontier models and infrastructure. Systems we keep still have to meet production standards for reliability, security, latency, scalability, and cost. Ready to build with us? Send us a quick introduction. Tell us who you are, what excites you about AI, and why you want to join FlowLinker. Let’s talk.

📌 AI Engineer (Quebec City)
🏢 FlowLinker
📍 Quebec City