Akamai TechnologiesRemote
Principal Software Engineer - Akamai Inference Cloud (Remote)
United States
Full-time
1 week ago
$148,000 - $308,000 USD
H1B Sponsor Likely
Key skills
AILLMMLOpsKubernetesAkamaiLeadership
About this role
Akamai Technologies is a leader in powering and protecting online experiences. They are seeking a Principal Software Engineer to serve as a technical leader for their AI inference platform, driving architectural decisions and optimizing AI workloads.
Responsibilities:
- Providing thought leadership, drive architectural decisions, and mentor engineers while delivering hands-on technical contributions
- Architecting and designing the core infrastructure of Akamai Inference Cloud, ensuring it is performant, compliant, economical, and explainable
- Providing thought leadership on AI inference optimization, model serving architectures, and establishing technical standards for the platform
- Making critical technical decisions on frameworks, tools, and approaches for AI workload deployment and global traffic orchestration
- Contributing hands-on to critical path development, code reviews, and architectural implementations
- Collaborating with cross-functional teams to define technical requirements and elevate team capabilities
Requirements:
- 12+ years of relevant experience and a Bachelor's degree or its equivalent
- Deep expertise in AI inference optimization, model serving, and LLM deployment at scale
- Thought leadership on AI inference optimization, model serving architectures, and establishing technical standards for the platform
- Expert-level proficiency with cloud-native technologies, Kubernetes, distributed systems, and architecting services at global scale with strict SLOs
- Solid opinions and proven experience building AI platforms developers love, including API design and cost optimization for compute-intensive workloads
- Excellent technical leadership with ability to mentor engineers, influence architectural decisions, and communicate effectively across teams
- Experience with building platforms for AI application developers (RAG, agents, fine-tuning workflow)
- Working knowledge of AI safety and practices, MLOps practices and AI model lifecycle management