Software Engineering Senior Manager

About this role: We are seeking a Software Engineering Senior Manager to lead engineering teams responsible for Digital Experience Protection (DEP) capabilities that protect customer interactions from sophisticated bots, account abuse, fraudulent automation, and emerging agent-driven threats. This is a senior technical leadership role combining engineering leadership, architectural depth, software-engineering expertise, production ownership, and digital threat protection. The successful candidate will move comfortably between organizational leadership, architecture and design reviews, implementation discussions, production reliability, threat analysis, and technology strategy. This leader will help evolve DEP beyond traditional bot detection toward protecting interactions among humans, applications, automated systems, and autonomous agents, while advancing scalable platforms and AI-enabled detection capabilities. This position is intended for an engineering leader who manages, rather than a general manager who happens to lead engineering teams . The successful leader will combine strong people leadership and technical judgment engaging constructively with architects and senior engineers, bringing alternative perspectives and respectfully challenging assumptions when appropriate. They will guide platform and AI strategy, and make consequential decisions involving customer experience, protection effectiveness, and production reliability. They will have the prowess to guide the engineering of AI-native detection capabilities, not simply manage the adoption of AI technologies. In this role, you will: Provide Technical and Architectural Leadership Lead engineering teams responsible for business-critical DEP platforms, services, APIs, detection capabilities, and integrations. Establish technical strategy aligned with business needs, customer experience, and the evolving threat environment. Lead architecture and design reviews covering scalability, resiliency, security, latency, observability, and maintainability. Maintain sufficient coding and technical depth to review implementations, APIs, detection logic, and AI-enabled solutions. Guide development of modular, API-first architectures that enable rapid integration of new signals, models, rules, vendors, and internal capabilities. Lead modernization of legacy and vendor-dependent capabilities while maintaining production stability and protection effectiveness. Advance Bot, Automation, and Abuse Defense Lead engineering strategy for detecting bots, scripted automation, credential-based attacks, account abuse, automated fraud, and emerging machine-driven threats. Guide layered detection and decisioning using network, device, behavioral, identity, account, transaction, and historical risk signals. Translate attack patterns, control gaps, and adversary behavior into scalable technical capabilities. Partner across fraud, cybersecurity, authentication, digital product, architecture, infrastructure, and application engineering. Balance protection effectiveness with customer experience, latency, operational complexity, and business risk. Measure control effectiveness and adapt defenses as adversaries evolve. Lead AI-Native Detection and Agent Strategy Lead development of AI- and LLM-based solutions that interpret user activity, behavioral signals, interaction sequences, and telemetry to identify suspicious or emerging behaviors. Determine where LLM reasoning, machine learning, deterministic rules, and behavioral analytics should be used independently or together. Guide production AI architecture, including model integration, grounding, tool calling, evaluation, observability, security, reliability, latency, and appropriate deterministic controls. Establish methods for measuring the accuracy, explainability, operational performance, and protection value of AI-based capabilities. Drive experimentation while establishing clear criteria for moving AI solutions into production. Prepare DEP for interactions involving humans, traditional automation, software agents, and autonomous AI agents. Develop approaches for evaluating automated interactions based on identity, intent, provenance, authorization, behavior, trust, and risk. Apply AI to improve detection engineering, investigation, threat analysis, testing, software delivery, and operational support. Build and Lead Strong Engineering Teams Recruit, develop, and retain engineers, technical leads, architects, and engineering managers. Build a culture in which leaders remain technically engaged and teams understand both the platforms and threats they address. Establish expectations for code quality, automated testing, deployment safety, observability, vulnerability remediation, documentation, and production ownership. Develop technical leaders capable of independently owning complex platforms and architectural decisions. Reduce knowledge concentration through secondary ownership, cross-training, reviews, rotations, documentation, and succession planning. Balance delivery with modernization, reliability, technical-debt reduction, and engineering capability development. Hold teams accountable for measurable technology and risk outcomes. Own Production and Platform Health Provide accountable leadership for the performance, availability, resiliency, and engineering health of DEP capabilities. Drive monitoring, capacity planning, resilience testing, incident prevention, root-cause analysis, and operational automation. Establish failure-handling and graceful-degradation strategies for internal and external dependencies. Lead trade-off decisions involving customer experience, protection effectiveness, and platform stability. Ensure incidents and control degradation result in durable technical and operational improvements. Shape Platform and Vendor Strategy Develop a balanced build, buy, and partner strategy for DEP. Evaluate solutions based on effectiveness, data and si