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Brightwheel is the largest platform in early education, trusted by millions of educators and families. The company operates as a vertical SaaS serving a $175B underserved market, with a mission to support childhood outcomes and working families. You will join the GTM engineering team as an AI-native software engineer focused on building AI solutions that directly impact business operations.
In this role, you will own meaningful problems end-to-end: from discovery and prototyping through launch, measurement, and iteration. You'll design and build AI services (retrieval, context, evaluation, guardrails) that power go-to-market operational workflows, enabling internal teams to operate at peak performance. You'll act as a hybrid PM+Eng+Data builder, owning the complete product loop—talking to customers and internal teams, defining success metrics, designing workflows and UX, shaping data and evaluation plans, and shipping iterative releases from prototype to production.
Key responsibilities include using AI to improve both how you build and what Brightwheel delivers, prototyping quickly to validate assumptions, and raising the bar for quality, reliability, security, privacy, and observability. You'll create shared abstractions and tooling for AI (prompt patterns, logging, monitoring, reusable components) so other engineers can build on a consistent foundation. You'll also shape data and system architecture to enable AI to safely stitch together signals across product, billing, support, and operations.
Required qualifications: 8+ years of professional software engineering experience with strong fundamentals across systems, data, APIs, product surfaces, and infrastructure. You must have owned production work from problem definition through launch and iteration, use AI tools and agents as a real part of your workflow, and demonstrate how you've increased velocity without lowering quality. You should be comfortable operating in ambiguity, communicate clearly across functions, and care deeply about privacy, security, reliability, and customer trust.
Preferred experience includes shipping AI-powered products or internal tools to production, working with retrieval, tool use, evaluation, monitoring, orchestration, or agent workflows, and experience in vertical SaaS domains like education, fintech, healthcare, or CRM. A portfolio demonstrating builder energy (personal projects, open-source work, demos) is valued.
Tech stack: AWS Bedrock and Bedrock AgentCore, LangChain/LangGraph, vector search, LangFuse, Cursor/Claude Code; Python with FastAPI, async workers; PostgreSQL, Redshift, Redis, DynamoDB; React with TypeScript.
