• Architect AI-integrated deployments: Design and support Qostodian implementations that connect to customer agent fleets, MCP-enabled tools, and autonomous security workflows—not just standalone installations • AI-accelerated customer success: Use LLMs, automation, and agentic tools to diagnose issues, generate configuration scripts, create custom integrations, and reduce resolution time from days to hours • Navigate complex enterprise architectures: Understand multi-cloud, hybrid, and agentic infrastructure where Qostodian is one node in a larger autonomous security ecosystem • Proactive technical guidance: Anticipate integration challenges, API changes, and architectural bottlenecks before they impact customers; provide best practices for MCP-based workflows • Bridge technical depth and business outcomes: Translate agentic architecture benefits into risk reduction metrics, compliance wins, and operational efficiency gains for executive audiences • Continuous learning and experimentation: Actively test emerging AI tools, agent frameworks, and integration patterns; bring insights back to Product and Engineering teams • Collaborate cross-functionally: Work with Support, Product, and Engineering to resolve complex issues, influence roadmap based on architectural trends, and share AI-driven workflow innovations • Drive renewals and expansion: Monitor customer health in high-complexity environments, identify growth opportunities enabled by AI capabilities, and support strategic account expansion • Conduct business reviews: Present technical architecture evolution, AI-driven value delivery, and roadmap alignment to ensure long-term customer success