Full Stack Engineer - Trust and Safety

About this role

Build systems that detect and prevent abuse across Calendly sign-up, booking, and messaging flows. The role also focuses on email and SMS deliverability, compliance, and cost management while balancing abuse prevention with a low-friction customer experience.

About the company

Calendly is a scheduling platform that automates meeting booking across calendars, reducing back-and-forth for sales, recruiting, and customer teams.

The team

Trust & Safety team, reporting to the Engineering Manager.

Stack

What you'll do

• Build and improve abuse detection systems for spam, phishing, bots, and fraudulent SMS traffic.
• Improve the reliability, deliverability, and compliance of email and SMS notifications.
• Measure detection performance on real traffic and balance false positives against false negatives.
• Respond to active abuse during on-call and develop durable fixes.
• Build tools that help Trust & Safety Operations review accounts and understand system decisions.
• Partner with Product, Operations, Data, and other product teams to define, deliver, and evaluate protections.
• Review implementation plans and pull requests and share learnings with the team.

What we're looking for

• 3+ years of professional software development experience building and operating production systems.
• Strong backend experience building services, APIs, and data-heavy workflows in a service-oriented architecture.
• Experience with Rails, Node/TypeScript, Go, or a comparable language or framework, and willingness to work across multiple technologies.
• Comfort with relational databases, SQL, and using data to evaluate changes.
• Analytical mindset and sound judgment balancing abuse prevention with customer friction.
• Commitment to maintainable code, thoughtful testing, and incremental delivery.
• Clear communication with technical and nontechnical partners.
• Comfort using AI tools critically and availability for an on-call rotation.

Nice to have

• Experience in trust and safety, fraud, spam, or abuse prevention.
• Experience with email or SMS delivery, deliverability, sender reputation, or messaging compliance.
• Experience with bot protection, rate limiting, or third-party risk and verification services.
• Experience building rules engines, risk scoring, or production ML-backed decisions.
• Experience using LLMs to classify or moderate user-generated content.
• Experience with GCP, Kubernetes, PostgreSQL, or Redis.