Job Description
We are not just predicting the future; we are building it. Zai Future Labs is seeking a visionary Senior 2026 AI Systems Architect to lead the charge in developing the next generation of autonomous, sentient-ready computing infrastructures. If you are passionate about pushing the boundaries of what is possible in the year 2026 and beyond, this is your opportunity to shape the trajectory of human-machine collaboration.
Responsibilities
- Design and architect scalable, high-performance AI infrastructure capable of supporting next-gen neural networks and quantum computing integration.
- Lead the research and implementation of 'AGI-ready' frameworks, ensuring systems are adaptable, ethical, and secure.
- Collaborate with cross-functional teams of quantum physicists, data scientists, and hardware engineers to bridge the gap between theoretical models and practical deployment.
- Define technical roadmaps for the 2026 product cycle, identifying emerging technologies and integrating them into our core architecture.
- Mentor senior engineers and lead code reviews to maintain the highest standards of engineering excellence and innovation.
- Oversee the deployment of edge computing solutions that bring AI capabilities to real-time, localized environments.
- Establish best practices for AI safety, bias mitigation, and regulatory compliance in emerging markets.
Qualifications
- Master’s or Ph.D. degree in Computer Science, Artificial Intelligence, Computational Neuroscience, or a related technical field.
- Minimum of 7 years of experience in full-stack system architecture, with a strong focus on machine learning operations (MLOps) and distributed systems.
- Deep expertise in Python, C++, and Rust, with proven experience in building large-scale training pipelines.
- Experience with quantum computing libraries (e.g., Qiskit, Cirq) and hybrid quantum-classical algorithms is highly preferred.
- Strong understanding of transformer architectures, generative models, and reinforcement learning.
- Excellent leadership skills with a track record of managing diverse, high-performing engineering teams.
- Ability to communicate complex technical concepts to non-technical stakeholders and executive leadership.