Applied AI Engineer

Bonfirevc

New York (NY)

On-site

USD 230,000 - 300,000

Full time

9 days ago

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Benefits offered by this job

Fully company-covered medical and dent

401(k)

Catered lunches and dinners

Job summary

Santé is hiring an Senior Applied AI Engineer to design, build, and scale agents powering our core merchant experience. You’ll develop production-ready agent and context-layer applications that turn each store’s sales history and catalog into profitable decisions.

You will own models from research to production, collaborating with engineers, PMs, and store owners to drive measurable merchant revenue gains and hours saved. Expect rapid development and a vibrant AI-driven setup.

Qualifications

5+ years building and shipping robust AI products.
Strong software engineering skills (TypeScript and/or Python).
Experience with the full AI lifecycle: data analysis, evaluation, monitoring.
Proven collaborator and communicator in cross-functional teams.
BS, MS, or PhD in Computer Science or related field.

Responsibilities

Design, build, and iterate on agents powering Santé’s core merchant experience.
Develop production agent and context-layer applications for store data.
Own the model lifecycle from research to production.
Collaborate with engineers, PMs, and store owners to drive measurable impact.
Stay at the forefront of ML/AI innovation and tooling.

Skills

TypeScript

Python

Agentic tools

Data analysis

Rigorous evaluation

Collaboration

Education

BS/MS/PhD in CS or Engineering

Tools

Next.js

tRPC

Prisma

PostgreSQL with pgvector

Vercel

Job description

Santé

All-in-one POS for liquor stores

Applied AI Engineer

Job type: Full-time
Role: Engineering, Full stack
Experience: 3+ years
Visa: US citizen/visa only
Salary: $230K - $300K
Equity: 0.10% - 0.25%
Location: New York, NY, US

About the role

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 store owners the insight they need to run a stronger business. This team also owns invoice OCR/CV (structured extraction from messy distributor invoices, with selectable 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:
- 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

Compensation

$220k – $300k + Meaningful equity

This range reflects the expected compensation for this role. Compensation within the range is determined based on experience, skills, and scope of responsibilities. In addition to base salary, we offer meaningful early-stage equity — this team's work is the foundation the company compounds on.

Benefits

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.

About the interview