Job Description
Are you ready to architect the backbone of tomorrow's intelligence? Nexus 2026 is seeking a visionary Lead AI Infrastructure Engineer to spearhead the development of next-generation neural networks and scalable cloud ecosystems. As we stand on the precipice of the 2026 era, we are building systems that don't just process data—they understand it. Join a team of elite engineers dedicated to pushing the boundaries of generative AI, quantum computing integration, and autonomous systems.
In this pivotal role, you will bridge the gap between cutting-edge machine learning research and robust, production-grade infrastructure. You will define the technical roadmap for our AI core, ensuring our platforms are not only powerful but resilient, secure, and infinitely scalable.
Responsibilities
- Architect and deploy high-performance, distributed computing systems for large-scale AI training and inference.
- Design and optimize Kubernetes clusters and serverless architectures to support real-time generative AI workloads.
- Implement advanced CI/CD pipelines to accelerate model deployment and reduce time-to-market.
- Collaborate with research scientists to translate theoretical models into efficient, scalable software solutions.
- Ensure system reliability, security, and data integrity across global edge nodes.
- Mentor a team of junior engineers and data scientists, fostering a culture of technical excellence and innovation.
Qualifications
- Master’s degree or PhD in Computer Science, Electrical Engineering, or a related field.
- 7+ years of experience in software engineering, with a strong focus on cloud infrastructure (AWS, GCP, or Azure).
- Deep expertise in Python, TensorFlow, PyTorch, and modern containerization technologies (Docker, Kubernetes).
- Proven track record of designing systems capable of handling petabyte-scale data processing.
- Experience with MLOps practices, including model versioning, A/B testing, and monitoring.
- Strong understanding of network protocols, security best practices, and high-availability architectures.