Senior AI Software Engineer, Product

About the role

Our team builds the platform that thousands of early education programs rely on every day to run their business, serve families, and support children’s growth. As a vertical SaaS company, brightwheel already sits in the middle of all the key workflows in early education: enrollment, billing, staffing, classroom planning, and family communication. We are now extending that foundation into a system of action – where software not only records what happened, but also anticipates work, recommends next steps, and takes safe, automated action on behalf of school leaders, teachers, families, and our internal teams.

We’re looking for an AI-native software engineer to join our product engineering team. This is a builder role for someone who wants to solve real customer problems and help define how AI changes the product experience for early education. You will build customer-facing product experiences that help school administrators, teachers, and families save time, make better decisions, and run stronger early education programs. You will partner closely with product, design, and customer-facing teams to turn ambiguous customer problems into shipped software with measurable customer impact.

The best candidates do not wait for perfect requirements. They prototype quickly, validate assumptions with users or internal teams, define success metrics, and iterate in production. They use AI agents, coding tools, scripts, and automation to move faster, while raising the bar for quality, reliability, privacy, security, and customer trust.

What you’ll do

• Own meaningful problems from discovery through launch, measurement, and iteration.

• Use AI to improve both how you build and what brightwheel can deliver.

• Prototype quickly, validate assumptions, and use working software to create clarity.

• Raise the bar for quality, reliability, security, privacy, observability, and execution.

• Build customer-facing workflows across enrollment, billing, classrooms, staffing, family communication, onboarding, or other core product areas.

• Partner with product, design, and customer-facing teams to turn ambiguous customer problems into shipped software with measurable impact.

   

You may be a good fit if you

• Have 2+ years of professional software engineering experience.

• Have strong engineering fundamentals and can reason across systems, data, APIs, product surfaces, and infrastructure.

• Have owned production work from problem definition through launch and iteration.

• Use AI tools and agents as a real part of your engineering workflow, not as a novelty.

• Can explain how you have increased your own velocity without lowering your quality bar.

• Have examples of automating your own work, your team’s work, or broader company workflows.

• Are comfortable operating in ambiguity and turning unclear problems into shipped software.

• Communicate clearly and work well across functions.

• Care deeply about privacy, security, reliability, and customer trust.

Strong candidates may also have

• Experience shipping AI-powered products, workflows, or internal tools to production.

• Experience with retrieval, tool use, evaluation, monitoring, orchestration, or agent workflows.

• Experience in vertical SaaS, education, fintech, healthcare, CRM, ecommerce, or another operations-heavy domain.

• A portfolio of personal projects, internal tools, open-source work, writing, demos, or side projects that shows builder energy and taste.

• Experience building customer-facing product experiences with measurable adoption or outcome impact.

• Experience improving web or mobile outcomes through architecture, tooling, shared patterns, or production feedback.

Technology

• Backend: Ruby on Rails, Sidekiq

• Data: PostgreSQL on Amazon RDS, Redis, and event and analytics pipelines

• Frontend: React with TypeScript

• Mobile: Native iOS with Swift and Android with Kotlin and Jetpack Compose

• Cloud and Infrastructure: Docker, Kubernetes on Amazon EKS, GitHub Actions and FluxCD for CI/CD, and AWS services such as S3, CloudFront, CloudWatch, and SNS

• AI and Automation: AWS Bedrock and other hosted large language models, vector search, orchestration and agent frameworks, and modern AI coding tools like Cursor, Claude Code, and Codex