Job Description
We are seeking a visionary Senior AI Infrastructure Engineer to architect the backbone of our next-generation autonomous systems. As we accelerate toward the 2026 vision, your expertise will define the operational scale and resilience of our neural networks. You will not just manage servers; you will engineer the digital nervous system of a company poised to redefine the technological landscape of the coming decade.
In this role, you will be at the intersection of hardware efficiency and software scalability. You will build the infrastructure that powers the next wave of generative intelligence, ensuring our platforms are robust, secure, and infinitely scalable.
Responsibilities
- Design and deploy scalable, fault-tolerant machine learning pipelines capable of handling exabyte-scale data streams.
- Lead the architectural transition to edge-computing environments to minimize latency in real-time AI inference.
- Implement and manage advanced Kubernetes-based orchestration for distributed AI workloads.
- Optimize hardware resource utilization through dynamic, autonomous allocation algorithms.
- Collaborate with quantum computing researchers to prepare software stacks for future hardware iterations.
- Establish rigorous security protocols for sensitive training data and model weights.
Qualifications
- 10+ years of experience in software engineering, with at least 5 years specifically focused on AI infrastructure and distributed systems.
- Deep proficiency in Python, Rust, and modern containerization technologies (Docker, Kubernetes).
- Proven track record of optimizing large-scale distributed systems for high availability and sub-millisecond latency.
- Extensive experience with major cloud platforms (AWS, GCP, or Azure) and serverless computing paradigms.
- Strong understanding of cybersecurity best practices within AI environments and model protection strategies.
- Experience with hardware acceleration (GPUs/TPUs) and GPU cluster management.