• Lead the execution of complex API and integration migrations to Azure, including refactoring patterns and coordinating cutovers to minimize downtime. • Implement API-led and event-driven integration patterns using Azure services, deployment tools, and monitoring frameworks. • Architect and secure APIs in Azure APIM using OAuth 2.0, Entra, mTLS, and robust API governance practices. • Operate and administer Azure platform components using Infrastructure-as-Code (IaC) tools like Terraform/OpenTofu, Azure CLI, and the portal. • Develop containerized Azure Functions and deploy integration workloads to Azure Kubernetes Service (AKS). • Design complex data transformations with reusable libraries, managing multi-level mappings and translations. • Automate CI/CD processes using GitLab and enforce engineering quality through unit, integration, and functional testing. • Establish actionable observability for APIs using Azure Monitoring and external tools like Splunk. • Champion the use of GenAI tools (like GitHub Copilot) to accelerate delivery speed and improve code quality safely. • Drive root-cause analysis and lead troubleshooting efforts to provide durable, preventative fixes for production incidents.

• Design and maintain enterprise interoperability architectures leveraging HL7 v2, v3, CDA, and FHIR standards. • Lead implementation of secure health data exchange solutions across VistA systems, COTS applications, and external partners. • Ensure compliance with VA Technical Reference Model (TRM), One-VA Enterprise Architecture, and federal security standards. • Develop and support HL7 interfaces, including integration with VistA modules such as TIU and other clinical systems. • Provide technical leadership and guidance to development teams on interoperability best practices and standards adoption. • Produce and maintain architecture documentation, including design patterns, interface specifications, and CONOPs. • Collaborate within Agile teams to identify risks, define technical milestones, and support delivery across the program lifecycle. • Take on additional tasks and responsibilities as needed to support team objectives and ensure the success of the project.

• Attract, recruit, ramp, and mentor a team of great Observability Architects from diverse backgrounds and experiences. • With our Engagement Management team, help define, build and execute impactful customer lifecycle frameworks. • Get the best out of your team with a servant-based leadership approach. Adopting a player/coach mentality will be critical here, ensuring that you balance your field responsibilities with the needs of your team. • Be responsible for retention and expansion. • Direct the bulk of your day-to-day work based on guidance and goals from leadership, owning the planning, actions and outcomes of the region. • Partner with the US Sales leadership on customer programs, marketing initiatives and community/company events to drive adoption and expansion within our customer base. • Executive sponsorship of key accounts in the region will be key to your success. The right candidate will be a thought leader to customers and internally within Grafana Labs. • Understanding and contributing to your key customers’ strategies for adoption of Grafana technologies. Developing programs and collateral to enable them to achieve their goals. • Ensure that your customers’ requirements are being met with our product through partnership with Product Management and Engineering. • Own and report on the quarter over quarter cadence of your team while they help prospects evaluate our software with demonstrations, technical deep dives, trials and POVs. • Educating and enabling viewers, editors, and architects how to leverage the Grafana stack. • Assist with building/modifying critical SLA dashboards within the production environment. • Work closely with our sales team to articulate the overall Grafana value proposition, vision, and strategy to customers. • Proactively communicate with customers and internal teams to provide a feedback loop on our products and the competitive landscape. • Work with the team to enhance documentation, write blog posts, record videos, contribute knowledge base articles, and create other public and internal enablement material.

• Provide engineering solutions to operationalize the latest GPU Computing products and software stacks • Ensure technical relationships with internal and external engineering teams • Assist systems, machine learning/deep learning engineers in building creative solutions based on NVIDIA technology • Be an internal reference for system administration, at-scale system analysis, and other datacenter and large-scale GPU-accelerated system solutions among the NVIDIA technical community