Senior II Software Engineer - Akamai Inference Cloud

The Akamai Inference Cloud team is part of Akamai's Cloud Technology Group. They build AI platforms for efficient, compliant, and high-performing applications that support customers in running inference models and empower developers to create advanced AI solutions effectively.

• Software engineering experience with distributed systems, cloud services, and platform engineering.
• Experience building and operating internet-facing platform services such as API gateways, ingress layers, reverse proxies, or service infrastructure.
• Expertise in cloud-native architectures, containerization, and orchestration technologies such as Kubernetes.
• Proven experience with modern DevOps practices, CI/CD pipelines, and infrastructure-as-code.
• Technical leadership skills including mentoring and promoting code quality.
• Experience designing and operating API platforms with authentication, authorization, traffic management, and service protection.
• Expertise in observability, monitoring, alerting, and debugging for large-scale distributed systems.
• Experience with capacity planning, performance analysis, and reliability engineering for production services.

• Bring software engineering experience with expertise in distributed systems, cloud services, and platform engineering.
• Build and operate internet-facing platform services such as API gateways, ingress layers, reverse proxies, or service infrastructure.
• Build scalable, high-performance systems with modern DevOps practices, CI/CD pipelines, and infrastructure-as-code.
• Mentor, promote code quality, and deliver effective solutions to address complex platform challenges.
• Design and operate API platforms, including authentication, authorization, traffic management, and service protection patterns.
• Implement observability, monitoring, alerting, and debugging practices for managing large-scale distributed systems.
• Perform capacity planning, performance analysis, and reliability engineering for production services.

Platform design and implementation:

• Design and implement critical platform components ensuring performance, scalability, and reliability.
• Drive technical decisions, selecting appropriate tools, frameworks, and approaches for AI inference workloads.
• Lead evolution of platform capabilities including authentication, load balancing, rate limiting, firewall integration, and externally facing API patterns.
• 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 for growth in traffic, models, and regional deployments.
• Lead Kubernetes-based orchestration patterns for platform services.
• Mentor and guide engineers through code reviews, design discussions, and technical problem-solving.