Engineering Manager, Bots & Fraud

Cloudflare•San Francisco, CA

About The Position

Cloudflare is hiring an Engineering Manager to lead a team building and scaling products for bot management, fraud detection, and abuse mitigation. The team helps customers determine whether Internet traffic comes from people, automated agents, or malicious actors. Its products address challenges such as unwanted scraping, controlling access for bots and AI agents, and identifying fraud and abuse while limiting friction for legitimate users. They use global network signals, threat intelligence, and machine learning to make probabilistic decisions in adversarial environments, and turn those signals into customer-facing analytics and controls. The role combines people management and technical leadership. The manager will recruit, mentor, and grow engineers; partner with Product Management to shape and deliver the roadmap; and work with detection and research teams to translate their signals into reliable, performant, accessible customer solutions. The systems include real-time services across Cloudflare’s global network, APIs and configuration, and high-volume data and analytics pipelines. The manager will collaborate across engineering, product, and customer-facing teams to deliver capabilities and improve customer outcomes and operational health. Cloudflare describes itself as a company on a mission to help build a better Internet, operating a large global network that powers and protects Internet properties. It values curiosity, iteration, practical use of AI in engineering, and sharing improvements across teams. The role is available in Austin, Texas; Washington, D.C.; and New York City. Washington, D.C. and New York City hires have an estimated annual salary range of $190,000–$261,000, subject to adjustment based on work location. The role is eligible for Cloudflare’s equity plan.

Requirements

Track record leading engineering teams, including hiring, onboarding, coaching, and supporting professional growth.
Strong software engineering foundation and experience designing, building, and operating large-scale distributed systems and services.
Experience taking projects from inception to production and overseeing execution to meet commitments in a fast-paced, iterative engineering environment.
Ability to connect business goals with technical decisions, explain the rationale and implementation, and make thoughtful tradeoffs when requirements are uncertain.
Ability to work across Product, Engineering, and other functions to align priorities, remove blockers, and deliver shared outcomes.
Clear communication with engineers, customers, and senior leadership, adapting technical detail to the audience.
Fluency using AI in engineering workflows and sound judgment about where it helps and where it falls short.
Curiosity about web security, bot management, fraud and abuse, and the evolving role of AI agents on the Internet; willingness to learn the domain.

Nice To Haves

Experience building bot management, fraud detection, application security, or other products that make decisions in adversarial environments.
Familiarity with HTTP, browser technologies, JavaScript, and tradeoffs between security, privacy, and user experience.
Experience integrating machine learning models into production systems or partnering closely with data science and machine learning teams.
Experience with high-volume data pipelines, analytics services, or columnar databases such as ClickHouse.
Experience with technologies such as Go, Rust, Python, Kafka, Kubernetes, and PostgreSQL.

Responsibilities

Lead, hire, mentor, and grow engineers through feedback, career development, and a culture of ownership and technical excellence.
Partner with Product Management to translate customer problems into incremental roadmap deliverables, balancing new capabilities with reliability, performance, and maintainability.
Provide technical leadership in design discussions and guide decisions on scalable distributed services, product integrations, APIs, and analytics.
Partner with detection and research teams to turn detection signals into actionable analytics and configurable customer controls.
Use customer feedback and production data with Product and detection partners to improve product effectiveness, reduce unnecessary friction, and make products easier to adopt.
Own operational health, including observability, safe releases, incident response, and follow-through on improvements.
Drive cross-team execution by resolving dependencies, aligning priorities, and working with customer-facing partners to address recurring product problems at their roots.
Collaborate across engineering and product teams to bring new capabilities into production and continuously improve the customer experience.

Benefits

Equity plan participation.
Medical/Rx insurance.
Dental insurance.
Vision insurance.
Flexible spending accounts.
Commuter spending accounts.
Fertility and family-forming benefits.
On-demand mental health support and Employee Assistance Program.
Global travel medical insurance.
Short- and long-term disability insurance.
Life and accident insurance.
401(k) retirement savings plan.
Employee stock participation plan.
Flexible paid time off covering vacation and sick leave.
Leave programs, including parental, pregnancy health, medical, and bereavement leave.