Job Description
Join the Architects of Tomorrow.
We are Zai Future Tech, a pioneer in next-generation artificial intelligence, seeking a visionary Senior AI Architect to define the roadmap for 2026 and beyond. You won't just be building models; you will be architecting the intelligent infrastructure that will power the global economy in the coming decade.
In this pivotal role, you will bridge the gap between theoretical AI research and scalable, production-ready systems. We are looking for a thought leader who thrives on complexity and is obsessed with pushing the boundaries of what is possible.
Why Join Us?
- Work on cutting-edge Generative AI and Autonomous Systems.
- Competitive compensation and equity package reflecting 2026 market standards.
- Flexible remote-first culture with HQ in the heart of SF.
If you are ready to shape the future of technology, apply today.
Responsibilities
- Strategic Roadmapping: Define and execute the technical roadmap for AI infrastructure, ensuring alignment with the company's 2026 vision and long-term goals.
- System Architecture: Design scalable, fault-tolerant, and high-performance AI systems capable of handling massive data throughput and complex model inference.
- Research & Development: Lead proof-of-concept (PoC) initiatives for emerging AI technologies, including Large Language Models (LLMs), Computer Vision, and Reinforcement Learning.
- Team Leadership: Mentor a team of senior engineers and data scientists, fostering a culture of innovation, technical excellence, and continuous learning.
- Collaboration: Partner with product managers, researchers, and stakeholders to translate business requirements into technical blueprints.
- Optimization: Drive performance optimization initiatives to reduce latency and improve model accuracy in real-time environments.
Qualifications
- Education: MS or PhD in Computer Science, Mathematics, or a related technical field.
- Experience: 8+ years of experience in software engineering, with at least 5 years focused on AI/ML architecture and deployment.
- Technical Proficiency: Deep expertise in Python, PyTorch, TensorFlow, or JAX. Experience with MLOps tools (Docker, Kubernetes, MLflow) is essential.
- AI Expertise: Proven track record designing and deploying production-grade models, specifically in NLP or Computer Vision.
- Problem Solving: Exceptional ability to troubleshoot complex system architectures and make high-stakes technical decisions.
- Communication: Excellent verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.