Senior II Software Engineer Lead

Akamai•Cambridge, MA

18h•$146,400 - $263,600

About The Position

The Senior II Software Engineer Lead will drive the design and implementation of critical components of Akamai Inference Cloud, a globally distributed AI inference platform. The role involves hands-on development and optimization of systems that provide OpenAI-compatible endpoints and orchestrate inference workloads across regions. The engineer will guide other engineers, influence technical direction, and ensure delivery of high-quality, scalable solutions. Akamai Inference Cloud is part of Akamai's Cloud Technology Group. The team designs, implements, deploys, and operates AI platforms that help customers run inference models and build AI applications with performance, compliance, and economic advantages. Akamai describes its FlexBase program as allowing employees to work from home, in an office, or in a combination of both, based on job needs.

Requirements

At least 8 years of relevant experience and a bachelor's degree or equivalent.
Solid proficiency in distributed systems, cloud services, and platform engineering.
Hands-on experience with AI inference, model serving, or LLM deployment, and working knowledge of inference frameworks such as TensorRT, vLLM, TorchServe, or Triton.
Expertise in containerization and orchestration technologies, including Kubernetes, Docker, and cloud-native architectures.
Proven experience building scalable, high-performance systems with modern DevOps practices, CI/CD pipelines, and infrastructure-as-code.
Technical leadership experience, including mentoring, advocating for code quality, and driving solutions to complex problems.
Familiarity with API design and development, including REST/gRPC patterns, GPU infrastructure, and hardware acceleration.
Knowledge of observability, monitoring, and debugging distributed systems.

Responsibilities

Lead the design and implementation of critical Akamai Inference Cloud platform components, ensuring performance, scalability, and reliability.
Drive technical decisions for the domain, selecting tools, frameworks, and approaches for AI inference workloads.
Mentor and guide team engineers through code reviews, design discussions, and technical problem-solving.
Implement and optimize containerized AI workloads using hardware-specific optimizations and integrate inference frameworks at scale.
Collaborate across teams to define technical requirements, contribute to platform standards, and ensure operational excellence.