Staff AI Product Builder

Role Overview

Staff AI Product Builder (Full Remote)

As a Staff-level AI product builder, you will own AI-powered improvements in core workflows, design and build cross-cutting AI services, and help shape the company’s data and system architecture.

Key Missions

• Design and build transversal AI services that power multiple product domains (e.g., classroom workflows, billing, and family communication).
• Own the end-to-end product cycle for the problems you tackle:
  • define success metrics
  • design the workflow and user experience
  • launch iterative versions
• Build shared abstractions and AI tooling (e.g., prompt models and common tools) so other engineers can ship faster with consistent foundations.

Responsibilities / What You’ll Do

• Turn ambiguous customer problems into clear technical plans and ship end-to-end experiences.
• Ensure craft and trust in delivered features by implementing evaluation and guardrails.
• Design secure, maintainable systems and leave behind reusable building blocks.
• Apply an outcomes-driven approach focused on helping preschools/childcare centers stay full, save time, and serve families better.

Requirements

• Staff-level full-stack builder who is AI-native and product-minded.
• Experience treating AI as part of your toolchain (AI coding assistants, IDEs, lightweight automation/orchestration).
• Hands-on LLM experience in real applications, including:
  • prompt and tool design
  • retrieval-style patterns (RAG)
  • evaluation and monitoring in production
• Strong computer science fundamentals (data structures, algorithms, systems design) and ability to operate across backend/data/UX.
• Security-minded with experience handling sensitive school, educator, and family data; design for least-privilege access.
• Track record of raising the bar for quality and operations:
  • secure, testable, maintainable code
  • automation/simplification of dev/test/ops workflows
  • writing/reviewing design docs
  • mentoring and contributing to hiring
• 5+ years of professional software engineering experience delivering medium-to-large production systems from problem statement to launch.
• Formal CS training (4-year CS degree or equivalent depth).
• Proven experience shipping AI-powered products to production.

Nice-to-Haves (Implied)

• A portfolio of personal AI projects, open-source work, or writing showing applied AI thinking in real-world settings.
• Familiarity with defining and validating success metrics through prototypes and customer/internal stakeholder collaboration.