The engineering team is looking for an AI Engineer who can build the LLM and agentic capabilities that bring intelligence into the Quartermaster experience. This role is less about traditional ML modelling and more about the hands-on software engineering needed to get LLMs into production: prompting, agentic workflows, and API-based model integration, shipped through our existing Python/TypeScript stack.This is a hands-on role for an ambitious engineer, someone with a solid SaaS software background who's looking to grow into owning intelligent features end-to-end. You don't need a modelling or academic ML background; you need solid engineering fundamentals, real experience shipping LLM-backed features, and the initiative to help figure out where intelligence belongs in the product next.

If we’re not our customer’s best choice, then we’re wasting their time. Empowerment – Any win we achieve needs to be first and foremost a win that we deliver to others, starting with our customers, and their long term best interests.VACATION AND BENEFITS We offer 30 days of PTO annually, which can be used for vacation, personal days, or illness. In addition, our benefits plan covers health, dental and wellness to add that extra pep in our step, and help us sleep at night.We have a tech allowance benefit to help set you up for work.We have pregnancy and parental leave policies, and we’re ready to support your family’s next stage of growth.Design, build, and ship LLM-powered and agentic features across the Quartermaster product — maintenance guidance, contractor matching, document understanding, conversational experiences, and similar user-facing intelligenceIntegrate LLM APIs and agentic frameworks into our Python/TypeScript SaaS stack,



following our existing engineering patterns and conventionsTake ownership of these features from API design and prompt/agent design through testing, deployment, and monitoring in productionCollaborate with product and engineering to scope what to build next, not just execute a fixed specApply sound software engineering practice (testing, code review, incremental delivery) to LLM-based features — including evaluating and regression-testing prompt and agent behavior, not just conventional code pathsHelp establish internal patterns and conventions for building and maintaining LLM/agentic features as the team grows this capabilityRequired Qualifications Hands-on experience building with LLMs — prompting, API integration, and/or agentic workflows (not limited to a research or notebook context)Strong software engineering fundamentals, with hands-on experience in PythonBackground in SaaS web development — building and shipping features in a production web applicationExperience with agentic frameworks (e.LangChain, PydanticAI, LangGraph, or equivalent)Experience deploying and operating production services in a cloud environmentAwareness of LLM API cost, latency, and rate-limit tradeoffs when designing production featuresComfortable working across the stack — from backend APIs to the LLM/agent layerA product-engineering mindset: you care about shipping a feature that works for real users, not just a model that scores well offlinePreferred (Nice to Have) Experience with a Python async web framework (FastAPI or similar) and a document database (MongoDB or similar)Experience with TypescriptExperience with Claude Code or similar AI-assisted development toolsExperience with vector search / retrieval pipelinesPrior experience in a small-team or early-stage SaaS environment, owning features end-to-endYou’re mission-driven and looking to solve the mission’s hardest problems.

📌 Ai Engineer (Winnipeg)
🏢 hireVouch
📍 Winnipeg