• Lead Engineering Execution: Own sprint planning, standups, retrospectives, backlog grooming, and cross-functional coordination. Drive delivery across multiple product areas, including AI agents, workflow automation, integrations, and UI/backend systems. • Build & Maintain Engineering Metrics: Design and maintain dashboards and reporting systems covering capacity, velocity, lead time, deployment quality, resource utilization, and other performance KPIs. Identify trends and surface risks early through data-driven insights. • Technical Leadership & Mentorship: Provide architectural guidance for full-stack and AI/ML components. Shape design decisions, enforce high code quality, and ensure scalable and compliant infrastructure. • Process Optimization & Operational Excellence: Identify bottlenecks and friction points across teams. Implement process improvements and reinforce engineering best practices to improve speed, stability, and collaboration. • Cross‑Functional Collaboration: Collaborate closely with Product, Security, and Compliance to meet business requirements and regulatory needs (e.g., SOC2, HIPAA). Ensure all deliverables meet enterprise-grade standards. • Support Team Growth & Scalability: Help onboard and grow engineering talent, especially junior and mid-level engineers. Maintain high standards of execution as the organization scales. • Self‑Starter Mindset: Take ownership of undefined or evolving problems, propose and implement solutions independently, and adapt quickly in a fast-paced environment.