Founding AI Engineer

**We’re Hiring: Founding AI Engineer** **Location:** Remote within Canada ONLY **Compensation:** Competitive salary and equity package FlowLinker is building the intelligence layer industrial automation companies use to define customer solutions before they reach CRM, CPQ, engineering, or delivery. Industrial sales and engineering teams make complex decisions based on incomplete conversations, scattered documents, technical constraints, product knowledge, and years of accumulated experience. Too often, this knowledge is lost between opportunities or remains concentrated in the minds of a few experienced employees. FlowLinker captures that knowledge, structures it, validates it against company-specific rules, and resurfaces it when teams need to make their next technical or commercial decision. We are backed by **Antler Canada** and have access to more than **$5 million in technology credits** from leading AI, cloud infrastructure, developer-tooling, and enterprise software providers. This is not a chatbot or a thin RAG interface. We are building production AI systems that must interpret ambiguous industrial language, reason across structured and unstructured information, apply domain-specific policies, identify missing information, and produce outputs that teams can confidently use. We are looking for a **Founding AI Engineer** to help build, scale, and shape the technical direction of these systems. **What you will work on** You will work closely with the founders and engineering team to: - Design and build production AI capabilities across the workflows FlowLinker delivers to its customers - Develop systems combining LLMs, retrieval, structured knowledge, schemas, policy rules, and deterministic validation - Improve entity extraction, requirement classification, product matching, contextual reasoning, and multi-step decision workflows - Build evaluation systems to measure accuracy, consistency, hallucination risk, and knowledge drift - Design pipelines for meeting transcripts, technical documents, product catalogs, customer requirements, and company-specific knowledge - Improve the latency, reliability, observability, scalability, and cost of our AI infrastructure - Take ownership of capabilities from early experimentation through production deployment and customer adoption - Contribute directly to our technical architecture, engineering standards, and long-term AI strategy **What we are looking for** You may be a strong fit if you have: - Experience building and deploying AI or machine-learning products in production - Strong **Node.js, TypeScript, and software-engineering fundamentals** - Hands-on experience with LLM APIs, retrieval systems, embeddings, structured outputs, tool use, and evaluation - Experience turning ambiguous product and customer requirements into reliable technical systems - A strong understanding of where probabilistic models should—and should not—be trusted - The ability to work across AI experimentation, backend engineering, data pipelines, infrastructure, and product delivery - High ownership, strong technical judgment, and comfort operating in an early-stage company - The ability to move quickly without sacrificing reliability or engineering discipline Experience with knowledge graphs, ontology design, search infrastructure, agentic workflows, industrial automation, manufacturing, robotics, or technical sales is valuable, but not required. **What matters most** We are not looking for someone whose experience stops at prompting models or connecting an LLM to a vector database. We want someone who cares about whether a system: - Reaches the correct interpretation - Applies the right technical and organizational context - Identifies what remains unknown - Produces traceable and defensible outputs - Behaves reliably inside real customer workflows You should be comfortable challenging assumptions—including ours—and selecting the simplest architecture capable of meeting the required level of accuracy and reliability. **The environment** You will build with a modern, production-grade AI stack and have access to more than **$5 million in cloud infrastructure, AI, developer-tooling, and enterprise software credits**. This gives our engineering team the freedom to experiment with frontier models, infrastructure, and emerging technologies while still holding every system to production standards for reliability, security, latency, scalability, and cost. **How we work** This is not a conventional 9-to-5 role. We are an early-stage company building a technically ambitious product for demanding industrial customers. This role requires substantial ownership, urgency, flexibility, and personal accountability. There will be periods of intense execution around product releases, customer deployments, and major technical milestones. We care about outcomes rather than rigid working hours, but anyone joining at this stage must understand the level of commitment required. In return, you will have meaningful influence over: - The core AI architecture - Product and technical strategy - Engineering practices and culture - The continued development of the AI team - How applied AI is deployed within a complex and underserved industry You will work directly on foundational technology, collaborate closely with customers, and see your work move rapidly from technical design into real operational use. This is a high-ownership role for someone who wants to solve difficult applied-AI problems and help define how engineering knowledge is captured, validated, and reused across an organization. **Interested?** Send us a brief introduction, examples of AI systems you have built, and a clear explanation of what you personally owned—from technical design through production deployment.