Job Description
Are you ready to architect the future? Zai Future Systems is seeking a visionary Senior AI Architect to lead our strategic initiatives for the 2026 Vision program. We are building the foundation for the next generation of artificial intelligence, and we need a leader who can translate complex algorithms into scalable, real-world solutions that define the year 2026.
In this role, you will bridge the gap between theoretical research and production-grade deployment, ensuring our AI infrastructure is robust, secure, and future-proof. You will work closely with cross-functional teams to integrate cutting-edge technologies into our core ecosystem.
Why join us?
- Shape the trajectory of AI development through the 2026 horizon.
- Competitive compensation package and equity options.
- Work with state-of-the-art hardware and cloud infrastructure.
- Flexible work environment in the heart of innovation.
Responsibilities
- Define and execute the 2026 technical roadmap for our AI division, aligning with long-term business goals.
- Architect scalable machine learning pipelines and deep learning frameworks capable of handling petabyte-scale data.
- Lead the migration of legacy systems to next-generation cloud-native AI architectures.
- Mentor and mentor junior engineers, fostering a culture of innovation and technical excellence.
- Collaborate with product managers to translate strategic vision into technical specifications.
- Ensure system reliability, security, and performance optimization for all AI deployments.
- Stay ahead of industry trends, specifically focusing on advancements expected to materialize by 2026.
Qualifications
- 10+ years of experience in software engineering and machine learning architecture.
- Proven track record of leading large-scale AI projects from concept to production.
- Deep expertise in Python, TensorFlow, PyTorch, and distributed computing.
- Strong understanding of cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes).
- Experience with NLP, Computer Vision, or Reinforcement Learning is highly preferred.
- Master’s degree or Ph.D. in Computer Science, AI, or a related field.
- Excellent communication skills with the ability to present complex technical concepts to non-technical stakeholders.