Jobs at Clover Security

Own Clover’s digital marketing ecosystem across website, SEO, GEO, lifecycle automation, paid performance channels, conversion optimization, analytics, attribution, and funnel infrastructure. The role manages website journeys, landing pages, forms, CRM workflows, lead routing, budgets, experimentation, and performance reporting while supporting content and product teams with digital execution.

Build and own scalable, production-grade frontend experiences for Clover’s SaaS product. Responsibilities include designing and implementing features end to end, driving frontend architecture, improving component patterns and performance, collaborating with Product, Design, and Backend, and raising standards for accessibility, consistency, testing, quality, and delivery velocity.

Analyze AI agents and product features to identify performance patterns, edge cases, and improvement opportunities. Define AI performance metrics, build scalable analysis tools and pipelines, and translate findings into prioritized product direction. Partner with product, engineering, customers, and field teams to improve customer value and growth. The role also evaluates AI and ML product quality, supports cross-functional decisions, and may mentor analysts or establish analytical standards.

Build and own scalable backend systems, APIs, data pipelines, and AI-driven services for Clover’s security platform. Responsibilities include end-to-end feature delivery, architecture design, testing, deployment, monitoring, observability, reliability improvements, performance tuning, and cost optimization. Collaborate with Product, Frontend, and AI/ML teams to deliver secure, high-quality SaaS features in an ambiguous, fast-moving environment.

Own the technical customer journey from discovery and demos through proof-of-concept, onboarding, and expansion. Partner with Account Executives, present to technical and executive stakeholders, lead proofs-of-concept, support deployments, create enablement materials, translate customer feedback for product and engineering, and influence messaging, go-to-market strategy, and roadmap priorities.

Conduct deep application and product security research across codebases, architectures, integrations, data flows, permissions, and AI agentic workflows. Identify risks missed by traditional scanners, investigate AI-assisted development security issues, maintain threat-pattern and detection logic, and translate findings into product capabilities, customer guidance, technical writing, evaluations, talks, and go-to-market insights.