• Partner with C-Level executives as a key operational leader, driving innovation and advancing AXS’ engineering strategy. • Define the engineering roadmap, balancing long-term vision with near-term priorities across product development, infrastructure, security, and compliance. • Oversee engineering execution to ensure delivery of high-quality, scalable software products that meet productivity, growth, financial, and roadmap objectives. • Lead the design, implementation, and continuous improvement of end-to-end engineering processes, with clear KPIs to measure and drive excellence. • Build and empower high-performing global teams, fostering a culture of innovation, collaboration, and continuous learning. • Collaborate with Product, Ticketing Strategy, Sales, Operations, AEG, and other partners to ensure strong outcomes and alignment. • Drive operational effectiveness through best practices, disciplined execution, and process improvements that increase productivity and reduce inefficiencies. • Translate business goals into actionable engineering initiatives, ensuring technical direction is aligned with organizational priorities. • Provide clear communication and progress updates to the CTO and senior leadership. • Manage operating budgets and resources effectively, ensuring financial accountability and sustainable growth.

• Implementing and maintaining platform components for Akamai Inference Cloud, with a focus on scalability, reliability, and operability. • Contributing to services across ingress, gateway, and data plane layers under the guidance of senior engineers. • Supporting the development of platform capabilities such as authentication, traffic handling, and API service functionality. • Helping build and improve data plane APIs, including interfaces aligned with OpenAI-compatible patterns and other supported standards. • Writing clean, maintainable, and well-tested code for cloud-native services running in containerized environments. • Assisting with observability by contributing metrics, logging, tracing, dashboards, and operational diagnostics for distributed systems. • Supporting Kubernetes-based deployment and orchestration of platform services in production environments. • Collaborating with teammates in code reviews, design discussions, testing, and incident support to improve platform quality and operational excellence.

• Design and implement core capabilities for a globally distributed AI inference platform. • Drive technical decisions for your domain, selecting appropriate tools, frameworks, and approaches for AI inference workloads. • Lead the evolution of platform capabilities including authentication, load balancing, rate limiting, and firewall integration. • Design and improve data plane APIs, including OpenAI-compatible interfaces and other standards. • Define and advance platform observability through metrics, logging, tracing, monitoring, and operational diagnostics. • Drive capacity planning and scalability strategies to support growth in traffic, models, and regional deployments. • Lead Kubernetes-based orchestration patterns for platform services. • Mentor and guide engineers on the team through code reviews, design discussions, and technical problem-solving.

• Leading the design and implementation of critical platform components for Akamai Inference Cloud, ensuring performance, scalability, and reliability. • Driving technical decisions for your domain, selecting appropriate tools, frameworks, and architectural approaches for secure, scalable, and high-performance inference platform services. • Leading the evolution of platform capabilities including authentication, load balancing, rate limiting, firewall integration, and externally facing API patterns. • Designing and improving data plane APIs, including OpenAI-compatible interfaces and other standards required to support diverse inference and AI application workloads. • Defining and advancing platform observability through metrics, logging, tracing, monitoring, and operational diagnostics for distributed systems at scale. • Driving capacity planning and scalability strategies to ensure the platform can support growth in traffic, models, and regional deployments. • Leading Kubernetes-based orchestration patterns for platform services, helping ensure efficient, resilient, and operable deployment of containerized workloads. • Mentoring and guiding engineers on the team through code reviews, design discussions, and technical problem-solving.