• Design, automate, and operate secure self-service AWS platform capabilities. • Own the foundation for governed multi-account provisioning and federated access. • Combine AWS Control Tower, AWS Organizations, and reusable Infrastructure as Code templates. • Create a scalable platform service to allow application and engineering teams to utilize secure cloud accounts.

• Design and implement RAG (Retrieval-Augmented Generation) pipelines using modern vector databases and embeddings • Build and optimize LLM-powered applications (chatbots, copilots, automation agents) • Leverage tools like Claude, GPT, and AI coding assistants to accelerate development and improve code quality • Develop agentic AI workflows using frameworks that enable reasoning, tool usage, and multi-step decision-making • Architect and deploy AI solutions using Azure AI Foundry / Azure OpenAI / Azure ML • Manage scalable deployments using Azure Kubernetes Service (AKS), Docker, and Helm • Implement semantic search and vector indexing using tools like Qdrant or Azure Cognitive Search • Build model-agnostic AI routing layers • Build and maintain full-stack applications integrating AI services • Use AI tools for code generation, refactoring, debugging, and optimization • Build and maintain CI/CD pipelines (Azure DevOps) for AI applications

• Own Our Azure Infrastructure • Lock Down Security & Identity • Be Our Safety Net • Keep Everything Connected • Be the Go-To Expert • Show Up When It Counts

• Own Our Azure Infrastructure, architecting WWF's Azure environment • Lock Down Security & Identity by configuring Microsoft Entra tenants and managing SSO through Azure Enterprise Apps • Be Our Safety Net by designing backup strategies and disaster recovery playbooks • Keep Everything Connected by troubleshooting networking across VNETs, sites, and tenants • Be the Go-To Expert for complicated Azure and M365 issues • Show Up When It Counts for occasional after-hours or weekend work for critical outages