Alexander Calhoun

Lead performance and scale strategy for Red Hat OpenShift AI and associated AI platform components. • Define and execute benchmark frameworks for distributed AI systems including multi-agent orchestration, RAG pipelines, vector databases, Postgres-backed data stores, and model inference engines such as vLLM • Evaluate end-to-end system performance and isolate component-level behavior across heterogeneous deployments • Analyze performance variability across cloud providers and infrastructure configurations • Drive optimization initiatives to improve throughput, latency, scalability, and resource efficiency • Establish performance requirements and capability targets aligned with product strategy • Integrate AI-driven analytics into performance workflows to accelerate large-scale data analysis and root cause identification • Partner with engineering and product leadership to position Red Hat as a platform for next-generation AI applications

Technical Leadership: Define and execute the technical roadmap for optimizing performance and scalability within an in-vehicle operating system, ensuring the platform meets rigorous automotive standards for reliability and efficiency. Product Ownership: Own and prioritize the backlog for performance and scalability improvements, balancing the reduction of technical debt with the delivery of key features that enhance the system’s capabilities. Team Management: Lead and mentor a team of engineers focused on pushing the limits of in-vehicle system performance, fostering a culture of continuous improvement and technical innovation. Cross-functional Collaboration: Collaborate closely with product, hardware, and infrastructure teams to align performance and scalability goals with the overall in-vehicle system vision and customer requirements. Risk Management & Optimization: Anticipate and address risks related to system performance and scalability as the system evolves. Continuously optimize the operating system to ensure it can handle increasing complexities and user demands in the automotive environment. Execution & Delivery: Drive the successful execution of projects aimed at enhancing the in-vehicle operating system’s performance, ensuring on-time, high-quality delivery that aligns with business and customer objectives.

- Established a comprehensive engagement model for performance investigations, addressing gaps in resource planning and compiling a backlog of ongoing investigations. - Played a pivotal role in aligning strategic objectives with team goals, particularly in the context of expanding supported platforms for the RHIVOS program. - Demonstrated influential leadership in navigating discussions with key stakeholders, including platform providers and MVP Customers, to align on strategic approaches crucial for program success. - Actively engaged in continuous learning, participating in mentorship programs and project-specific training to enhance skills and knowledge. - Authored insightful articles on embracing Agile for Performance Engineering, contributing to knowledge transfer within the performance department. - Contributed to and advocated the migration of the performance department to adopt Agile methodologies and capacity planning, contributing to enhanced efficiency and quality assurance.

• Openshift Containerized Storage (OCS) • Benchmark development for cloud storage • Creation of data warehouse and statistical analysis

• RedHat Ceph Storage • Performance and scalability testing • Test Automation

• Scrum Master • Software integration and test • Informal/formal software acceptance testing •. Software installation and configuration • Architect/implemented automated testing infra