Engineering Manager, Automation Intelligence

About the Role
This position offers the opportunity to lead the development of an innovative intelligence platform focused on distinguishing legitimate AI agents and automated traffic from malicious bots and other online threats. You will manage a high-impact engineering team responsible for delivering advanced detection capabilities, classification systems, and APIs to help enterprises navigate an increasingly automated internet. Your role will involve guiding the product from beta through general availability and commercial launch while ensuring exceptional detection accuracy, reliability, and scalability. By combining strategic leadership with strong technical judgment, you'll establish quality-driven engineering practices and champion an AI-native development model. This fully remote opportunity allows for direct collaboration with engineering leadership and the chance to shape a crucial product as well as the future of software engineering practices.

Accountabilities:

• Product Delivery & Launch Readiness: Own the engineering roadmap from beta to standalone commercial launch, partnering with product management on requirements, estimates, prioritization, delivery sequencing, and launch-readiness criteria.
• Service Reliability & Performance: Define and validate the service's operational limits, including throughput, latency, rate limiting, availability targets, and service-level objectives (SLOs) to meet production requirements.
• Detection Quality & Accuracy: Establish a continuous detection quality framework using representative test datasets, automated testing, regression suites, and monitoring to maintain and improve detection performance.
• Automation Coverage & Classification: Guide detection capabilities for AI agents, assistants, stealth automation, headless browsers, and other frameworks. Evolve classification systems to provide context, confidence levels, identity verification status, and reason codes.
• Safe Deployment & Continuous Improvement: Manage staged rollouts of detection updates using feature flags, rollback procedures, and measurable release criteria. Incorporate customer feedback and detection errors into prioritized engineering improvements.
• Team Leadership & Development: Lead, coach, and develop a small team of senior engineers, manage recruitment as the team grows, and establish clear ownership, accountability, and professional growth opportunities.
• Engineering Standards & Operational Excellence: Introduce effective engineering practices, including technical specifications, code review standards, repository ownership, and performance benchmarks covering delivery speed, throughput, predictability, failure rates, and recovery time.
• Cross-Team Collaboration: Establish effective working agreements with adjacent engineering teams, clarify shared responsibilities, and progressively reduce dependencies for independent development and deployment.
• AI-Native Engineering Leadership: Lead an agent-first development workflow in which AI tools support specification, coding, review, and security checks, with appropriate human oversight for critical changes. Maintain and improve tools and review frameworks.
• Measurement & Knowledge Sharing: Evaluate AI-assisted development effectiveness against engineering baselines, conduct performance reviews, and document lessons learned for broader engineering practices.
• API Design & Integration Standards: Ensure all product interfaces follow a contract-first approach with OpenAPI specifications, automated breaking-change detection, generated documentation and SDKs, ensuring accessibility for developers and AI agents.
• Observability & Executive Communication: Own service observability through logs, metrics, traces, and SLOs. Communicate engineering progress, technical trade-offs, detection quality, and launch readiness to leadership and product partners.

Requirements:

• Engineering Management Experience: At least three years of experience managing software engineers, including senior and staff-level contributors, with a proven track record of delivering complete products.
• Strong Technical Foundation: At least eight years of software engineering experience prior to or alongside management. Ability to critically assess technical designs, engage in architectural discussions, and resolve trade-offs.
• Relevant Domain Expertise: Strong experience in areas such as bot detection, fraud prevention, web security, browser engineering, or high-volume API services, particularly in adversarial environments.
• Quality-Driven Engineering: Experience building measurement-driven engineering processes, encompassing test datasets, precision and recall metrics, regression testing, and monitoring.
• Hands-On AI Coding Experience: Regular use of AI coding agents with practical understanding of their strengths and limitations in software development workflows.
• Product & Cross-Functional Leadership: Ability to collaborate closely with product managers and customer-facing teams, making dependencies and priorities explicit.
• Communication & Decision-Making: Excellent written and verbal communication skills, with the ability to document and explain technical performance and release readiness to both technical and non-technical stakeholders.
• Team Building & Autonomy: Proven ability to develop high-performing teams, establish ownership structures, recruit effectively, and allow experienced engineers independence in execution.
• Preferred Bot Detection & Security Experience: Direct experience with bot detection, management, anti-automation products, CDNs, WAFs, fraud prevention, or security platforms.
• Preferred AI Agent Knowledge: Familiarity with AI agent ecosystems and how autonomous agents interact with websites and APIs.
• Preferred Browser & Automation Expertise: Understanding of browser internals, headless browsers, and detection techniques for automated activity.
• Preferred API & Platform Experience: Experience with API-first products, OpenAPI specifications, SDKs, and similar interfaces.
• Preferred Organizational Experience: Experience establishing a new engineering team from a larger organization, separating codebases, and maintaining cross-team relationships.
• Preferred Business Environment: Background in a high-growth SaaS company serving enterprise clients.

Benefits:

• Fully Remote Work: Work within a globally distributed, remote-first organization, subject to local employment requirements.
• Strategic Leadership Opportunity: Report directly to the VP of Engineering and lead a vital product initiative with significant decision-making autonomy.
• Product Ownership & Impact: Guide an emerging product from beta to commercial launch with dedicated product management support.
• Experienced Engineering Team: Lead an established group of senior engineers, with plans for team expansion.
• Innovation & Technical Leadership: Help establish an AI-native engineering model, influencing development standards across the engineering organization.
• Professional Growth: Develop expertise in AI detection, fraud prevention, high-volume services, and advanced engineering management.
• Inclusive Work Environment: Join a workplace that values diverse perspectives, professional respect, and equal opportunity.
• Important Employment Considerations: Some countries may be excluded for regulatory reasons, and visa sponsorship is not available. Eligibility, compensation, and contractual arrangements should be confirmed during recruitment.