• Build and Scale the AI Developer Tools Team: Hire, onboard, and develop a high-performing engineering team from the ground up with expertise in AI/LLM integration, platform engineering, and developer experience; establish team culture, technical standards, and operating norms • Ship AI-Powered Developer Tools: Deliver production-ready AI agents for developer productivity (automated PR reviews, code generation, documentation), observability insights (anomaly detection, root cause analysis), and operational automation (deployment pre-reviews and failure investigations, incident response assistance) • Build Self-Service AI Developer Tools Platform: Create and operate the foundational infrastructure that enables teams across Docker to build, deploy, host, and scale their own AI developer tools including deployment frameworks (ArgoCD/GitOps), observability integration (Grafana), security controls, cost management, and operational tooling • Drive Platform Adoption and Developer Experience: Establish the AI Developer Tools platform as the default path for teams building AI-powered tooling; deliver self-service capabilities, comprehensive documentation, templates, and best practices that reduce time-to-production from weeks to days • Partner on AI Strategy and Technology: Work closely with engineering leadership and Agent Dev technical leadership to align on AI technology choices, architectural patterns, and integration strategies; stay current on LLM advancements and developer tooling trends • Explore Productization Opportunities: As internal AI developer tools demonstrate value, partner with product management and go-to-market teams to evaluate commercial viability; prototype, validate, and transition successful internal tools into customer-facing product offerings • Deliver Measurable Impact: Define and track success metrics for both AI developer tools (adoption rates, productivity gains, time saved) and platform capabilities (time-to-deploy new tools, number of teams using platform, operational efficiency) • Cross-Functional Collaboration: Partner with product engineering teams (Hub, Registry, Cloud/AI, Scout, Accounts & Billing), platform teams (Infrastructure, Security, Data), and product leadership to understand requirements, gather feedback, and align on priorities • Operational Excellence: Ensure reliability, security, and performance of AI developer tools and the hosting platform; establish SLOs, monitoring, and incident response for production AI systems serving internal developers • Team Development and Culture: Mentor and grow engineers on your team; foster a culture of experimentation, rapid prototyping, and learning; attract diverse talent excited about AI and developer experience