Scribd
Staff Backend Engineer (Payments and Billing)
San Francisco · Staff+ · Contract
Sponsorship not specifiedDetected 1 day ago
PythonJavaGoRubyDistributed SystemsBackend DevelopmentSQLNoSQLPostgreSQLMySQLDatadogPlatform EngineeringAgentic AIComplianceLeadershipCollaborationMentoring
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odds of building a lasting career here
40Risky
Cap-exempt (no lottery)0
Sponsors this role90
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70
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About the role
- Because our systems move money and sit in PCI scope, we hold AI-generated work to the same human-review, correctness, and security bar as anything else we ship.
Responsibilities
- Lead the technical architecture and implementation of Scribd's payments and billing systems, the backbone of our subscription business.
- Design, build, and operate backend services that power subscription payments at global scale.
- Own billing lifecycle, global payments, invoicing, reconciliation, and financial reliability, integrating with multiple providers (Stripe, Adyen, Braintree) and supporting international currencies and local methods.
- Lead agentic engineering on the team: use AI agents across design, implementation, testing, debugging, and operations, and help the team adopt workflows that make us measurably faster without lowering the bar on correctness or security.
- Build shared AI leverage for payments, such as agent skills for alert triage, incident investigation, and anomaly detection, and runbooks, documentation, and context that agents can use reliably.
- Contribute these to Scribd's shared skills marketplace rather than building one-off tools.
- Foster a culture of technical excellence while driving scalable, resilient, and observable financial systems that enable teams to move fast, simplify complexity, and deliver revenue with confidence.
- Partner with Product, Finance, Risk, Platform, and Analytics to deliver secure, reliable financial flows, leveraging data, metrics, and telemetry to uncover trends, resolve anomalies, and guide the team with clarity and foresight.
- Mentor engineers, shape cross-team technical strategy, and tackle some of the hardest scaling and security challenges in the company, including raising the bar on how the team designs, reviews, and verifies AI-assisted work.
- Has 8+ years of backend engineering experience, with deep expertise in building and scaling distributed systems for financial or mission-critical workloads.
Requirements
- Our four products - Scribd®, Slideshare®, Everand™, and Fable - help billions of people across the globe move beyond access and into insight, application, and expertise.
Benefits
- Comprehensive health, dental, and vision coverage
- Mental health support and disability coverage
- Generous paid time off, including vacation, sick time, holidays, winter break, volunteer time, and sabbaticals
- Paid parental leave and family support benefits
- Retirement matching and employee equity
- Learning and development programs and professional growth opportunities
- Wellness and home office stipends
- Modernize legacy systems and eliminate technical debt to improve velocity and scalability, using AI agents to accelerate migrations, refactors, and test coverage where they make sense.
- Scribd Flex (flexible work model)
Company info
- The Payments & Billing team at Scribd powers our subscription revenue engine by delivering the systems that manage billing lifecycles, global payment processing, and financial reliability across Scribd, Everand, Slideshare, and Fable.
- Our focus areas include payment processing at scale, invoicing, reconciliation, fraud prevention, compliance, and support for international currencies and payment methods.
- We partner closely with Product, Finance, Risk, and Platform Engineering to ensure that millions of readers worldwide can reliably access our services every day.
- We're an agentic engineering team.
- AI agents (Claude Code, shared agent skills, and integrations with tools like Datadog, Sentry, and Stripe) are part of how we design, build, test, triage, and operate every day.
- Build shared AI leverage for payments, such as agent skills for alert triage, incident investigation, and anomaly detection, and runbooks, documentation, and context that agents can use reliably. Contribute these to Scribd's shared skills marketplace rather than building one-off tools.
- Brings a strong foundation in data modeling, transactional consistency, and high-throughput architectures, with hands-on SQL (e.g., MySQL, PostgreSQL) and familiarity with NoSQL and caching.
- Has strong coding ability in at least one modern backend language such as Ruby (preferred), Java, Go, or Python, with a focus on clean, maintainable, and secure code.
- Has hands-on experience with agentic engineering tools and workflows in a real production setting. You use AI agents daily, can explain how you choose a tool or approach for a task, and know where these tools break down.
- Has the judgment to rigorously validate AI-generated code, protect sensitive data, and recognize when a change needs deeper investigation or shouldn't be delegated to an agent at all. You can explain and own every line you ship, whoever or whatever wrote it.
- Has multiplied a team's effectiveness by establishing patterns, tooling, or review practices that others adopted, including for AI-assisted development.
- Communicates clearly and collaborates across product, finance, risk, and platform teams, influencing both technical and business decisions.
- Contributes to cross-team initiatives (mentoring, architecture review groups, knowledge sharing) that shape Scribd's engineering culture.
- Have strong coding ability in Ruby.
- Have deep experience designing and operating payment or billing systems.
- Have integrated with major payment service providers (Stripe, Adyen, Braintree, PayPal) and managed multi-currency or local payment methods.
- Bring knowledge of compliance and security standards (PCI DSS, encryption, tokenization).
- Understand fraud prevention strategies (chargebacks, retries, card fingerprinting, abuse detection).
- Have led large-scale migrations between payment providers or billing systems with minimal customer impact.
- Have built agent skills, MCP integrations, or AI-assisted on-call and incident workflows that other engineers adopted.
- Have designed human-in-the-loop or AI code-review and merge controls in a regulated or PCI-scoped environment.
- Understand AI-specific security risks, such as prompt injection, secrets or PII leaking through agent context or logs, and over-permissioned agent credentials.
This listing is sourced directly from Scribd's careers page and normalized into a canonical job model.