B
Brightwheel
Principal AI Software Engineer (Product)
Skills
KotlinE-commerce WebsitesSwiftDockerRuby on RailsReactRubyTypescriptIOSPostgreSQLRedisData AnalysisAIAWSGitHubKubernetesCRM
2 months ago
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Important information
Contract type:
Permanent
Salary:
$194,000 – $263,000 / year
Location:
United States
Work mode:
Onsite
Published on:
17 August 2026
What they need
- You are a Principal Engineer who is both AI-native and relentlessly product-minded. You turn ambiguous, cross-team opportunities into clear technical direction, and then you prove the path by building
- You care about the flagship experiences you ship, and you obsess over the shared “paved highway” that makes it easy for the teams around you to ship safe, reliable AI over and over again
- You will make brightwheel measurably more valuable to schools, centers, educators, and families by delivering AI-powered capabilities that move business outcomes—for example retention, enrollment conversion, payment success, operational efficiency, and support burden
- This is not a research role or a “build cool demos” role; success is defined by impact in production
- Own outcomes end-to-end. Take responsibility for turning high-leverage opportunities into shipped, adopted capabilities with clear measurement, iteration loops, and sustained improvement—not one-time launches
- Define the AI technical direction for your organization. Translate customer problems into a practical strategy, reference architectures, and a roadmap that multiple teams can execute against, with minimal guidance
- Drive build-versus-buy decisions. Recommend when to partner on models and tooling versus when to build differentiated capabilities (data flywheels, evaluation systems, workflow-specific intelligence), backed by evidence from fast, hands-on spikes
- Lead by implementation. Rapidly prototype and ship reference implementations to prove feasibility, de-risk decisions, and raise your teams’ expectation for speed and ambition
- Help build the paved highway. Contribute shared foundations—evaluation harnesses, retrieval and context patterns, safety guardrails, observability, and developer experience—so teams can ship reliable AI features repeatedly and independently
- Raise the bar across your organization. Mentor senior and staff engineers, lead design reviews for your teams, help establish standards for quality and safety, and align stakeholders to drive adoption
- We work with:
- Backend: Ruby on Rails, Sidekiq
- Data: PostgreSQL on Amazon RDS, Redis, and event and analytics pipelines
- Frontend: React with TypeScript and Emotion
- Mobile: Native iOS (Swift) and Android (Kotlin with Jetpack Compose)
- Cloud & Infrastructure: Docker, Kubernetes on Amazon EKS, GitHub Actions and FluxCD for CI/CD, and AWS services such as S3, CloudFront, CloudWatch, and SNS
- AI & Automation: AWS Bedrock and other hosted large language models,, orchestration and agent frameworks, and modern AI coding tools like Cursor, Claude Code and Codex- Have examples of automating your own work, your team’s work, or broader company workflows
- Have strong engineering fundamentals and can reason across systems, data, APIs, product surfaces, and infrastructure
- Care deeply about privacy, security, reliability, and customer trust
- Can explain how you have increased your own velocity without lowering your quality bar
- Are comfortable operating in ambiguity and turning unclear problems into shipped software
- Use AI tools and agents as a real part of your engineering workflow, not as a novelty
- Communicate clearly and work well across functions
- Have 8+ years of professional software engineering experience
- Have owned production work from problem definition through launch and iteration
- Experience improving web or mobile outcomes through architecture, tooling, shared patterns, or production feedback
- Experience building customer-facing product experiences with measurable adoption or outcome impact
- 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 with retrieval, tool use, evaluation, monitoring, orchestration, or agent workflows
- Experience shipping AI-powered products, workflows, or internal tools to production
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