Applied AI Engineer

About the Team

In this role, you will

• Apply state-of-the-art ML and LLM techniques to problems spanning: Merchandising intelligence (slow-mover detection, price and promotion recommendation, competition and seasonality signals); Document understanding (invoice OCR and structured extraction across LLM engines); Retrieval and ranking (embedding-based product matching on pgvector, catalog dedup, contextual recommendations)
• Merchandising intelligence (slow-mover detection, price and promotion recommendation, competition and seasonality signals);
• Document understanding (invoice OCR and structured extraction across LLM engines);
• Retrieval and ranking (embedding-based product matching on pgvector, catalog dedup, contextual recommendations)
• Build agent capabilities on top of Santé's Manager Agent platform — task generation, review workflows, and chat over each store's own data
• Build the evaluation harness for both offline and online techniques, designing experiments 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 looks something like this

• 5+ years building and shipping robust AI products for large-scale, user-facing or data-driven products
• Strong software engineering skills (TypeScript and/or Python, production-quality codebases, collaborative development) and experience using agentic coding tools for large-scale parallel development
• In-depth experience with the full AI lifecycle: data analysis, rigorous evaluation, and ongoing monitoring and improvement
• Proven collaborator and communicator; excels in high-velocity, cross-functional teams
• Curious, driven by end-user and product impact, and passionate about advancing the state of applied ML and AI
• BS, MS, or PhD in Computer Science, Engineering, or a related field (or equivalent experience)

Even better

• Experience with LLM context engineering or harness engineering
• Experience in mid-training or post-training frontier open-source models
• Experience with large-scale user-centric and content-centric personalization challenges (user modeling, retrieval, content ranking)
• Experience with LLM observability and eval tooling (Langfuse or similar) in production
• Familiarity with our stack: Next.js, tRPC, Prisma, PostgreSQL with pgvector, Vercel
• Retail, pricing, or demand-forecasting domain experience — you know why moving a slow SKU matters to a store's cash flow

• Fully company-covered medical and dental benefits.
• 401(k)
• Catered Lunches and Dinners: Santé provides dinner each evening for employees who would like to eat and connect with the team. Lunch is provided on a weekly basis.