Job Description
Are you ready to architect the future of artificial intelligence? Nexus Horizon is seeking a visionary AI Systems Architect (2026 Vision) to lead our cutting-edge research division. As we push the boundaries of generative intelligence, multimodal learning, and autonomous systems, we need a leader who can design the infrastructure that powers the next decade of technology.
In this role, you will define the technical roadmap for our proprietary 2026 AI Framework, ensuring scalability, security, and ethical alignment. You will bridge the gap between theoretical research and production-grade deployment, working alongside world-class data scientists and engineers.
Why Join Us?
We are a remote-first, elite engineering collective focused on solving humanity's most complex problems through advanced AI. We offer competitive equity, unlimited PTO, and a culture that prioritizes radical innovation and cognitive diversity.
Responsibilities
- Design and implement scalable neural network architectures for the proprietary 2026 AI Framework, focusing on efficiency and low-latency inference.
- Lead the migration of legacy models to next-generation transformer-based systems and Agentic AI workflows.
- Define system-level requirements for data ingestion pipelines, ensuring high-fidelity training data management.
- Collaborate with cross-functional teams (Product, Security, Compliance) to ensure AI outputs align with global ethical standards and safety protocols.
- Optimize cloud infrastructure (AWS/GCP) to support massive-scale distributed training and inference.
- Conduct technical due diligence for acquisition targets and emerging AI technologies.
- Mentor senior engineers and define coding standards for AI infrastructure.
Qualifications
- Master’s or PhD in Computer Science, Mathematics, or a related field; or equivalent practical experience.
- 10+ years of software engineering experience, with at least 5 years specifically in AI/ML infrastructure.
- Deep expertise in Python, PyTorch, TensorFlow, and modern distributed computing frameworks.
- Proven track record of deploying large-scale LLMs and multimodal models in production environments.
- Strong understanding of MLOps, CI/CD pipelines, and containerization technologies (Docker, Kubernetes).
- Experience with quantum computing algorithms or edge AI deployment is a significant plus.
- Excellent communication skills with the ability to translate complex technical concepts for non-technical stakeholders.