Applied AI Engineer

Senior Applied AI Engineer - Applied AI About Santé Santé is the #1 operating system for local retailers. Our platform runs the entire store — point of sale, integrated payments, eCommerce, inventory management, delivery-app integrations, marketing, bookkeeping, and AI Agents — so the owners of liquor, grocery, and convenience stores can compete like the big chains without losing what makes them local. We're building a future where the corner liquor store has better technology than the national retailer: one place for selling to customers everywhere with AI agents that spots slow-moving inventory and creates the promotion to move it. Every feature we ship lands in real stores the same week, and the feedback loop is direct — our customers call us by name. We move fast and ship daily. AI-assisted engineering isn't a talking point here; agents like Devin, Claude, and Codex are part of how the team works every day, and engineers who master that leverage ship multiples of what they could alone. About the Team Applied AI owns the intelligence layer of Santé, including aspects of Merchandising, Custom Reporting, Ecommerce, and Agentic workflows. This is the team behind our AI Manager — a suite of production agents that handle end-to-end workflows like retail pricing strategies, creating marketing campaigns, maintaining SEO (eCommerce) and developing custom reports that give st [... source excerpt omitted ...] LLM engines) and embedding-based product matching. Nothing here is a demo: every model output lands in front of a real store owner making a real pricing decision. About the Role You'll design, build, and iterate on the agents powering Santé's core merchant experience. Working on this mission-critical team, you'll develop production agent and context-layer applications — turning each store's sales history, catalog, and market context into decisions that make independent retailers money. You'll own your models from research to production, and your work ships into stores the same week. In this role, you will Apply state-of-the-art ML and LLM techniques to problems spanning: M [... source excerpt omitted ...] ents and metrics (evals, QA playbooks, Langfuse tracing) that provide deep insight into recommendation quality and merchant impact Own the entire model lifecycle from research to production: data analysis, modeling, evaluation, offline/online testing, and iterative improvement — and build autonomous harnesses that let agent squads explore new problem spaces in parallel Collaborate cross-functionally with engineers, PMs, and store owners to ensure our AI drives measurable improvements in merchant revenue and hours saved Stay at the forefront of ML/AI innovation by evaluating and incorporating emerging research, models, and techniques into the product lifecycle Your background lo