Design, build, and ship production AI agents and ML systems for retail merchandising, document understanding, retrieval/ranking, and evaluation. Own full model lifecycle from research to production, build evaluation/observability, and collaborate with engineers, PMs, and store owners to drive measurable merchant impact.
Senior Applied AI Engineer - Applied AI
About Santé
About the Team
About the Role
In this role, you will
Your background looks something like this
Even better
Compensation
Benefits
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.
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.
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.
- 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.
- 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.
Similar Jobs
.png)
Artificial Intelligence • Healthtech • Machine Learning • Natural Language Processing • Software • Generative AI
Build AI-powered features and products for clinical documentation and medical coding. Develop LLM-driven agentic systems, APIs, services, and production infrastructure across healthcare revenue cycle workflows. Create evaluation frameworks and experimentation loops using statistical and data-driven methods to ensure reliability, auditability, and alignment with coding guidelines and user feedback. Collaborate with product, design, machine learning, clinical, and revenue cycle experts to deliver high-impact SaaS solutions.
Top Skills:
Agentic Ai SystemsAPIsEdiFhirHl7Large Language Models (Llms)PythonSaaS
AdTech • Artificial Intelligence
Conduct applied AI and machine learning research spanning multimodal intelligence, recommendation, ranking, prediction, foundation models, agents, and decision-making. Define research problems, evaluate and develop models using proprietary data, run rigorous experiments, create training signals and evaluations, and transition successful approaches into production systems. Collaborate with engineering and product teams while shaping the company’s research agenda and technical standards.
Top Skills:
Artificial IntelligenceCausal InferenceFine-TuningFoundation ModelsLarge Language ModelsMachine LearningMultimodal ModelsOptimizationRanking ModelsRecommendation SystemsReinforcement LearningRepresentation LearningRetrieval
Big Data • Information Technology • Software • Analytics
Own and deliver production-grade generative AI features that improve user experiences and operational intelligence. Scale systems handling terabytes of data, realtime querying and notifications, and high-performance search. Train, deploy, integrate, and monitor machine learning models while writing robust, tested software. Collaborate with product, engineering, deployment teams, and users to solve complex problems. This is an onsite role for candidates located in NYC.
Top Skills:
AirflowAmazon BedrockAmazon SagemakerAWSCeleryDjangoElasticsearchGenerative AiKafkaKubernetesLarge Language ModelsMapboxPostgresPulumiPythonReactReduxTerraform
What you need to know about the NYC Tech Scene
As the undisputed financial capital of the world, New York City is an epicenter of startup funding activity. The city has a thriving fintech scene and is a major player in verticals ranging from AI to biotech, cybersecurity and digital media. It also has universities like NYU, Columbia and Cornell Tech attracting students and researchers from across the globe, providing the ecosystem with a constant influx of world-class talent. And its East Coast location and three international airports make it a perfect spot for European companies establishing a foothold in the United States.
Key Facts About NYC Tech
- Number of Tech Workers: 549,200; 6% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Capgemini, Bloomberg, IBM, Spotify
- Key Industries: Artificial intelligence, Fintech
- Funding Landscape: $25.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Greycroft, Thrive Capital, Union Square Ventures, FirstMark Capital, Tiger Global Management, Tribeca Venture Partners, Insight Partners, Two Sigma Ventures
- Research Centers and Universities: Columbia University, New York University, Fordham University, CUNY, AI Now Institute, Flatiron Institute, C.N. Yang Institute for Theoretical Physics, NASA Space Radiation Laboratory
