Software Engineer II - Platform Anti-Abuse

The Core Infrastructure – Identity & Organizations (Core IO) pillar owns the foundational substrate for identity access organizations and platform integrity at Klaviyo. We manage the critical path of the user journey from login to enforcing permissions to operating within the correct organization and regional context so that the rest of the platform can move fast and stay secure.

Within Core IO the Platform Anti-Abuse (PAA) team defends Klaviyo's customers their recipients and Klaviyo's brand by preventing fraud abuse and violations of our Acceptable Use Policy and Terms of Service across all channels. We build the automated detection systems rules-driven enforcement services and shared platform tooling that keep Klaviyo's platform safe; and we partner closely with Compliance Security and product teams to make "doing the safe thing" the default for every new surface and API.

• Fight real adversaries at scale: Abuse patterns evolve constantly;bad actors adapt and so must your systems. You will build detection and enforcement capabilities that respond to emerging fraud patterns across email SMS and other channels combining rules signals and ML to stay one step ahead.
• Your work is the platform's safety net: The rules engine and enforcement services your team owns are consumed by messaging campaigns flows and nearly every sending channel at Klaviyo. Improvements you make protect millions of email and SMS recipients and directly affect platform trust and deliverability.
• Work at the intersection of rules ML and systems engineering: This role is unusually broad technically. You will build high-throughput Go services Python rules pipelines and integrate ML-based classifiers for content and URL abuse. Few platform roles combine adversarial problem-solving with this range of systems work.
• Automate policy enforcement at scale: Manual compliance review doesn't scale. We are building systems that automatically evaluate accounts against our Acceptable Use Policy and trigger the right enforcement actions; reducing human bottlenecks and making enforcement consistent across account types.

As a Software Engineer II on the Platform Anti-Abuse team you will:

• Own features end-to-end across design implementation rollout and observability for abuse detection and enforcement capabilities; rules classifiers enforcement pipelines and the platform services that other teams plug into.
• Extend abuse enforcement to new product surfaces: Help bring anti-abuse rules and enforcement to product areas where coverage is currently limited ensuring consistent policy application across channels.
• Build content and link abuse detection systems: Help design and implement detection capabilities for malicious URLs abusive image content and other content-level signals;combining perceptual hashing ML model integrations and rule-based approaches.
• Contribute to AUP automation and enforcement pipelines: Help build and scale the systems that automatically evaluate accounts against our Acceptable Use Policy reducing reliance on manual compliance review.
• Improve platform anti-abuse infrastructure: Evolve microservices rules orchestration layer and abuse observability pipelines; making them faster more reliable and easier for the team and compliance stakeholders to operate.
• Help define and refine standards for how other teams integrate with PAA's detection and enforcement APIs; so product teams can add abuse coverage to new areas without reinventing detection logic per service.
• Collaborate closely with partner teams: Work with Identity & Access Management (IAM) on authentication & authorization signals with Organizations on account lifecycle and policy enforcement and with Security and Compliance on AUP/TOS enforcement patterns.
• Improve reliability and observability of anti-abuse services by instrumenting metrics and alerts maintaining abuse impact dashboards and contributing to on-call rotations and incident reviews.

You are a mid-level software engineer who has shipped and supported production systems and who is motivated by building defenses against real-world fraud and abuse.

• Experienced systems builder: You have 2-5+ years of professional software engineering experience including building and operating backend or full-stack services in production.
• Strong fundamentals and debugging skills: You are comfortable reasoning about data models API design concurrency and failure modes and you can dig through logs metrics and traces to identify root causes and implement systemic fixes.
• Security and abuse motivated: You are energized by adversarial problem spaces;fraud detection policy enforcement content moderation and want to build systems that anticipate bad actors rather than just react to them.
• Platform and signal mindset: You think about detection not just as individual rules but as a system of signals coverage and feedback loops. You like building shared enforcement APIs and detection pipelines that product teams plug into making abuse prevention a reusable capability rather than something each team reimplements.
• Ownership and collaboration: You take responsibility for outcomes not just code. You are comfortable driving a project end-to-end coordinating with Compliance and Security stakeholders and communicating trade-offs clearly in design docs and pull requests.
• You've already experimented with AI in work or personal projects and you're excited to dive in and learn fast. You're hungry to responsibly explore new AI tools and workflows.

• 2-5+ years of professional software engineering experience.
• Proficiency in at least one of Python or Go and comfort working on backend and/or service-oriented systems including web services or APIs backed by relational databases and/or caches (e.g. MySQL Postgres Redis).
• Comfort reasoning about detection classification or enforcement systems;whether rules engines content evaluation or risk signals and the trade-offs between precision recall and system performance.
• Exposure to CI/CD pipelines and modern development workflows (code review testing deployments on-call participation or support).

You don't need all of these but experience in any of the following is a bonus:

• Experience building detection or classification systems; rules engines content classifiers anomaly detection or fraud/risk scoring and reasoning about signal quality false positive rates and coverage.
• Familiarity with ML model integration in production systems: calling model endpoints processing outputs in rules pipelines and monitoring model-driven decisions.
• Working with cloud-native infrastructure (AWS Kubernetes Terraform or similar) and building services designed to run at scale.
• Exposure to compliance or policy enforcement domains (AUP/TOS enforcement content moderation fraud detection) and how platform decisions in these areas are made and measured.
• Familiarity with observability stacks (Grafana Datadog Sentry Splunk) and using them to drive reliability and detection-quality improvements.
• Interest or experience in adjacent Core IO domains like Identity & Access Management or Organizations especially where they intersect with account security fraud signals and org lifecycle.

Many of these you'll use on day one; others you'll have opportunities to learn:

• Languages & frameworks: Python Django Go.
• Infrastructure & platform: AWS Kubernetes Terraform rules engine and enforcement service platform.
• Data & observability: MySQL Postgres Redis Kafka/event-driven messaging Grafana Sentry Splunk internal logging and metrics pipelines.

Klaviyo is a world-leading marketing automation platform that helps online businesses grow by building direct high-fidelity relationships with their customers over owned channels like email SMS and web. We make it easy for brands to store access analyze and act on their data to power highly targeted communications and long-term customer value.

This is a full-time onsite role based at Klaviyo's headquarters in Boston MA.

Klaviyo is committed to building a diverse and inclusive team and does not tolerate discrimination harassment or retaliation of any kind.

What We Do

Klaviyo (NYSE: KVYO) is the B2C CRM. Powered by its built-in data platform and AI Klaviyo combines marketing automation analytics and customer service into one unified solution making it easy for businesses to know their customers and grow faster. Klaviyo (CLAY-vee-oh) helps over 183000 brands like Mattel Glossier Daily Harvest and Liquid Death deliver 1:1 experiences at scale improve efficiency and drive revenue.

Why Work With Us

We refer to our employees as ‘Klaviyos’ and we make up a diverse community united around shared values: We’re curious collaborative driven innovative fun and fully ourselves at work. No matter which team you join your work won’t just impact Klaviyo. It’ll help empower our customers and enable creators across the globe to own their destinies.

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