Principal AI Software Engineer, Product

Cacheflow; United States; On-site; USD 120,000 - 170,000; Full time

Job summary

Cacheflow is seeking a Principal Engineer who is AI-native and product-minded. In this role, you will drive AI-powered capabilities that improve business outcomes for schools and educators.

Successful candidates will have deep technical intuition, 8+ years of engineering experience, and a proven track record of mentoring engineers. Join us to create impactful AI solutions in a dynamic environment!

Qualifications

• Deep intuition for why models fail, with experience predating the LLM boom.
• 8+ years of engineering excellence with end-to-end ownership of large systems.
• Experience formulating architectural strategy at the organization level.
• Track record of mentoring and hiring engineers to improve their skills.
• Proven record of shipping AI-powered products to production.

Responsibilities

• Own outcomes end-to-end and turn opportunities into shipped capabilities.
• Define AI technical direction and translate customer problems into strategies.
• Drive build-versus-buy decisions backed by evidence.
• Lead by implementation and rapidly prototype reference implementations.
• Help build shared foundations and raise the bar across the organization.

Skills

AI intuition

Engineering excellence

Architectural strategy

Mentorship

Production AI experience

Education

4-year CS degree or equivalent

Tools

Ruby on Rails

PostgreSQL

Redis

React with TypeScript

Docker

Kubernetes

Job description

Who You Are

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.

What You'll Do

You will make brightwheel measurably more valuable to schools, centers, educators, and families by shipping 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. Turn 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.

What You've Done

We are open to a variety of backgrounds, but strong candidates usually bring:

• Foundational AI Depth: You possess deep intuition for why models fail, gained from experience that predates the LLM boom. You have likely worked with classical NLP/ML, giving you the grounding to make sound architectural decisions.
• 8+ Years of Engineering Excellence: You have end‑to‑end ownership of large, business‑critical systems. You launch large‑scale and/or highly complex software that requires members of multiple teams to contribute, and you deliver largely independently with minimal guidance.
• Architectural Strategy: Experience formulating architectural strategy at the organization level. You have designed systems that required execution across multiple teams, and you regularly influence technical and product priorities.
• Mentorship and Hiring: A track record of mentoring senior and staff engineers and improving their skills, knowledge, and ability to get things done. You actively interview engineers and your judgment carries weight in debriefs.
• Production AI at Scale: A proven track record of shipping AI‑powered products to production. You understand the "last mile" of AI—evaluation, monitoring, and safety—and have built the tools that allow teams to sleep soundly at night.

Nice‑to‑haves

• Experience earlier in your career with model training, fine‑tuning, classical machine learning, or natural language processing—enough to have intuition for why models fail and how data and evaluation shape outcomes.
• A portfolio of real work (open‑source, demos, writing, talks, or shipped side projects) that shows taste, velocity, and how you think about applied AI systems end‑to‑end.
• Experience building shared internal platforms or frameworks (for example evaluation services, retrieval infrastructure, policy and safety guardrails, observability tooling) that became the default path for multiple teams.
• Formal training in computer science (4-year CS degree or equivalent depth in core CS topics).
• A strong bar for operational excellence: secure‑by‑default design, performance and cost discipline, testability, incident readiness, and a track record of improving development, testing, and on‑call practices for complex systems.

Technology

We work with:

• Backend: Ruby on Rails, Python
• Data: PostgreSQL on Amazon RDS, Redis, and event and analytics pipelines
• Frontend: React with TypeScript
• Mobile: Native iOS and Android
• 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

Equal Opportunity Employer

Brightwheel is committed to creating a diverse and inclusive work environment and is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity, gender expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Protecting Our Applicants

Please be aware of recruiting scams impersonating Brightwheel. All legitimate communications come from @mybrightwheel.com addresses, and we never ask for payment or sensitive personal data as part of our hiring process. If you suspect fraudulent contact, reach out to [e-mail]. Thank you for helping us keep our applicant community safe.