Job Description
The Opportunity
We are at the precipice of a technological revolution. As Zai Horizon Labs, we are not just building software for today; we are architecting the foundational infrastructure for the 2026 Predictive Era. We are looking for a visionary Lead Architect to spearhead the development of next-generation autonomous systems capable of anticipating market shifts and consumer behaviors before they occur.
In this role, you will bridge the gap between theoretical AI research and scalable enterprise deployment. You will be responsible for designing the neural backbone of our 2026 ecosystem, ensuring our platforms are not just reactive, but prophetic.
Why Join Us?
- Impact First: Your work will directly shape the operational landscape of Fortune 500 clients in 2026.
- Future-Proof: Work on bleeding-edge technologies including Predictive LLMs and Quantum-ready architectures.
- Elite Team: Collaborate with Ph.D. researchers and ex-FAANG engineers pushing the boundaries of possibility.
Responsibilities
- Architect Predictive Frameworks: Design and implement high-availability, distributed systems capable of processing real-time data streams to generate accurate 2026-era forecasts.
- Lead R&D Initiatives: Spearhead research into Generative Adversarial Networks (GANs) and Reinforcement Learning to enhance system autonomy.
- Optimize Neural Topology: Continuously refine model architecture to improve latency, accuracy, and energy efficiency for edge computing environments.
- Technical Strategy: Define the technical roadmap for our 2026 product suite, ensuring alignment with business goals and emerging industry standards.
- Mentorship: Guide a team of senior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Stakeholder Communication: Translate complex technical concepts into strategic insights for executive stakeholders and clients.
Qualifications
- Education: Master’s or Ph.D. in Computer Science, Mathematics, or a related field with a focus on AI or Computational Statistics.
- Experience: Minimum 7+ years of experience in software engineering, with at least 3 years leading technical teams or architecture projects.
- Technical Mastery: Deep expertise in Python, PyTorch, TensorFlow, and distributed computing frameworks (Kubernetes, AWS/Azure/GCP).
- Predictive Modeling: Proven track record of designing and deploying complex predictive models and machine learning pipelines.
- Problem Solving: Demonstrated ability to solve ambiguous problems with innovative, scalable technical solutions.
- Communication: Exceptional written and verbal communication skills, capable of presenting to diverse audiences.