Staff Applied AI Engineer

About the role

Clover is building AI that acts on live merchant data at enterprise scale. You'll be a hands-on technical leader for applied AI on the Point of Sale platform. You'll define the architecture for AI across inventory, menu, and ordering, and build the systems that modernize how merchants run their business.

Responsibilities

• Own and drive technical architecture, design, implementation, testing, and deployment.
• Contribute towards AI Strategy & Roadmap, and deliver the applied AI portfolio.
• Design tool layer for agents writing to inventory — change proposals, permissions, rollback, audit.
• Build the retrieval layer (RAG) — agent output grounded in merchant data, current as it changes.
• Define behavioral contracts, build the evals that prove them, and ship on evidence, not demos.
• Engineer multimodal ingestion — photos, PDFs, spreadsheets into canonical data, reviewed where required.
• Build the decision layer on model output: recommendations merchants understand, trust, and act on.
• Instrument, operate, and stay on call for what you ship — tracing, cost budgets, live quality.
• Extend the shared multi-agent framework, contribute upstream, and use coding agents well.
• Coach and mentor engineers, growing their skills and careers in applied AI.
• Establish the patterns, guardrails, and components peers adopt.

Requirements

• Education: BS in computer science, engineering, math, physics, or equivalent practical experience.
• Senior Technical Leadership: 10+ years in software development, 3+ leading complex production systems.
• Engineering Foundations: Algorithms, data structures, Kubernetes, REST APIs, microservices.
• Stack: Python and a JVM language (Java, Kotlin, Scala); MySQL, MongoDB, and vector databases.
• Problem Solving: Analytical skills to root-cause systems that fail differently on identical input.
• Production Agent Ownership: An LLM system that writes to a system of record, with real users.
• Evaluation-Driven Development: Specs and contracts, evals that gate releases, statistical judgment.
• AI Systems Operations: Tracing, live quality monitoring, latency/cost budgets, regression detection.
• Risk Judgment: Blast radius on writes to a system of record; prompt injection; security and privacy.
• Agentic Coding Fluency: Steering