• Take cloud problems, investigate deeply, explain root causes clearly, and propose practical solutions • Own work end to end, drive it to completion, and communicate progress consistently • Build, operate, and improve GCP infrastructure, with some AWS support as needed • Support Kubernetes workloads on GKE and help teams run reliable, cost effective systems at scale • Work with core GCP building blocks including: • Kubernetes and containerized workloads • Queueing and messaging systems such as Google Pub Sub, Amazon SQS, RabbitMQ, or similar • Relational database systems like Postgres and Microsoft SQL Server • Data and storage systems such as object storage and BigQuery • Networking components including load balancers, web application firewalls, and traffic routing • Use logs, metrics, and tracing to troubleshoot production systems and improve performance and reliability • Identify opportunities to simplify architecture, reduce operational overhead, and improve scalability • Bring curiosity and follow through to understand how cloud resources work and why they behave the way they do • Maintain a habit of using AI tools to think, build, and ship faster—it’s your default, not an afterthought.

• Build the Internal Platform: Evolve our CI/CD ecosystem (GitHub Actions, ArgoCD) into a seamless, self-service platform that supports rapid deployment of microservices and AI-driven applications. • Execute Snowflake Infrastructure: Own the infrastructure side of Snowflake, including account provisioning, access controls, and network architecture, ensuring a solid foundation for our data and application engineering teams. • Automate FinOps Governance: Go beyond monthly reports by implementing "governance-as-code." Write automated policies and scripts that actively manage resource lifecycles, tag compliance, and prevent wasteful cloud spend before it happens. • Advance Infrastructure as Code: Manage and scale our IaC (Terraform), with modular, reusable patterns that allow developers to provision what they need within guardrails. • Support AI Velocity: Ensure our infrastructure can keep pace with the high-velocity creation of AI tools and applications, managing segmentation, dependency connections, and compute scaling efficiently.

• Design, develop, test, deploy, maintain, and improve our cloud-based infrastructure, focusing on high availability, low latency, and cost-effectiveness. • Collaborate closely with engineering and research teams to integrate infrastructure components with product features, ensuring optimal system performance and user experience. • Be the subject matter expert in infrastructure when designing new products and introducing new technology to our existing product line. • Develop automation scripts, tools, and frameworks to streamline deployment, monitoring, and maintenance processes. • Implement robust security measures, adhering to industry standards and best practices, to safeguard sensitive data and prevent potential vulnerabilities. • Analyze performance metrics, identifying areas for optimization and proposing data-driven improvements. • Participate in code reviews, contribute to open-source projects, and mentor junior engineers. • Stay up-to-date with emerging trends, technologies, and methodologies, applying this knowledge to enhance our infrastructure capabilities.

• Transform technology into opportunity as an Infrastructure Engineer with GDIT • Provide system administration and development/maintenance support of Commander, Navy Installation Command (CNIC) G2 applications • Perform root cause analysis to provide resolutions for production issues on CNIC applications • Support F5 implementation of G2 in Data Center • Coach and mentor System Administrators on best methodologies • Participate in strategic planning sessions for development of the application architecture and roadmap • Present solution designs to stakeholders for input, buy-in and sign-off