Senior II Software Engineer Lead - Akamai Inference Cloud

New
Remote/PolandFull-TimeLead
Salary not disclosed
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Job Details

Experience
8+
Required Skills
KubernetesCI/CDDevOpsDebuggingDistributed Systems

Requirements

  • 8+ years of software engineering expertise with advanced proficiency in distributed systems, cloud services, and platform engineering
  • Deep experience building and operating internet-facing platform services such as API gateways, ingress layers, reverse proxies, or service infrastructure
  • Advanced expertise in cloud-native architectures, incorporating containerization and orchestration technologies such as Kubernetes
  • Proven experience building scalable, high-performance systems with modern DevOps practices, CI/CD pipelines, and infrastructure-as-code
  • Exhibit technical leadership by guiding, promoting code quality, and delivering solutions for intricate platform challenges
  • Experience designing and operating API platforms, including authentication, authorization, traffic management, and service protection patterns
  • Extensive expertise in observability, monitoring, alerting, and debugging processes for large-scale distributed systems
  • Experience with capacity planning, performance analysis, and reliability engineering for production services

Responsibilities

  • Lead the design and implementation of critical platform components for Akamai Inference Cloud, ensuring performance, scalability, and reliability
  • Drive technical decisions for your domain, selecting appropriate tools, frameworks, and architectural approaches for secure, scalable, and high-performance inference platform services
  • Lead the 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 required to support diverse inference and AI application workloads
  • Define and advance platform observability through metrics, logging, tracing, monitoring, and operational diagnostics for distributed systems at scale
  • Drive capacity planning and scalability strategies to ensure the platform can support growth in traffic, models, and regional deployments
  • Lead Kubernetes-based orchestration patterns for platform services, helping ensure efficient, resilient, and operable deployment of containerized workloads
  • Mentor and guide engineers on the team through code reviews, design discussions, and technical problem-solving
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