Job Description
Are you ready to shape the technological landscape of the future? Zai Core Systems is seeking a visionary Senior AI Architect to lead our 2026 Initiative. We are building the next generation of cognitive infrastructure, and we need a leader who can bridge the gap between theoretical breakthroughs and scalable production environments.
In this pivotal role, you will define the architectural blueprint for our upcoming AI ecosystem, ensuring performance, security, and scalability. You will work closely with a world-class team of researchers and engineers to deploy models that redefine industry standards. If you are passionate about the future of AI and thrive in a fast-paced, high-impact environment, we want to hear from you.
Why join us?
- Work on cutting-edge AI research with real-world application.
- Competitive compensation and equity packages.
- Flexible remote-first culture with state-of-the-art equipment.
- Opportunity to mentor the next generation of AI talent.
Responsibilities
- Architectural Leadership: Design and oversee the implementation of scalable machine learning infrastructure tailored for the 2026 product roadmap.
- Model Optimization: Drive the deployment and optimization of large language models and generative AI systems to ensure low latency and high throughput.
- Roadmap Execution: Translate complex research concepts into actionable technical strategies and engineering milestones for the 2026 timeline.
- System Integration: Integrate AI components into broader software ecosystems, ensuring seamless interoperability with existing data pipelines.
- Talent Development: Mentor junior engineers and data scientists, fostering a culture of continuous learning and technical excellence.
- Security & Compliance: Implement rigorous security protocols to protect proprietary data and ensure compliance with industry standards.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, Machine Learning, or a related technical field.
- Experience: Minimum of 5+ years of experience in designing and implementing large-scale machine learning systems.
- Technical Skills: Proficiency in Python, PyTorch, TensorFlow, and experience with distributed computing frameworks (e.g., Kubernetes, Apache Spark).
- Architecture: Strong understanding of cloud architecture (AWS, GCP, or Azure) and microservices design patterns.
- Problem Solving: Demonstrated ability to troubleshoot complex technical challenges and optimize system performance under pressure.
- Communication: Exceptional ability to communicate complex technical concepts to non-technical stakeholders and cross-functional teams.