Software Engineer

Akamai powers and protects life online. Leading companies worldwide choose Akamai to build, deliver, and secure their digital experiences helping billions of people live, work, and play every day. With the world's most distributed compute platform from cloud to edge we make it easy for customers to develop and run applications, while we keep experiences closer to users and threats farther away.

• Bring 2+ of software engineering experience, with a solid foundation in backend systems, cloud services, or platform engineering.
• Show proficiency in building and debugging distributed or service-oriented applications.
• Have familiarity with cloud-native technologies such as containers, Kubernetes, and modern deployment workflows.
• Demonstrate experience developing APIs or backend services with attention to reliability, performance, and maintainability.
• Show understanding of core operational practices including testing, CI/CD, monitoring, and troubleshooting.
• Have familiarity with observability concepts such as metrics, logs, and tracing in production systems.
• Bring interest in internet-facing platform services such as ingress, authentication, load balancing, or API infrastructure.
• Show curiosity about AI inference platforms, model serving systems, or infrastructure used to support LLM and inference workloads.

• 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.