Job Description
We are pioneering the technological landscape of the 2026 era. Nexus Horizons is seeking a visionary Lead Architect to spearhead our Advanced General Intelligence (AGI) division. In this high-impact role, you will define the architectural paradigms for next-generation neural systems, ensuring scalability, ethical alignment, and unprecedented performance. If you are ready to move beyond current limitations and build the cognitive infrastructure of tomorrow, we want to hear from you.
Why Nexus Horizons?
We offer a competitive benefits package including equity, remote-first flexibility, and access to our proprietary quantum-ready computing clusters. Join a team of elite engineers and researchers dedicated to solving the unsolvable.
Responsibilities
- Architectural Vision: Design and implement scalable, fault-tolerant AI architectures for AGI research and production environments.
- Model Optimization: Lead initiatives to optimize large language models and neural networks for real-time, high-stakes decision-making.
- R&D Leadership: Collaborate with a cross-functional team of data scientists, ethicists, and security experts to define the roadmap for Project 2026.
- System Integration: Integrate disparate AI modules into a cohesive, unified cognitive system capable of adaptive learning.
- Talent Mentorship: Mentor junior engineers and foster a culture of continuous innovation and technical excellence.
- Compliance & Safety: Ensure all systems adhere to rigorous safety standards and regulatory compliance frameworks.
Qualifications
- Education: Master’s or PhD in Computer Science, Mathematics, or a related field with a focus on Artificial Intelligence.
- Experience: 8+ years of experience in software engineering, with at least 5 years specifically in machine learning and deep learning systems.
- Technical Mastery: Proficiency in Python, C++, and experience with deep learning frameworks (PyTorch, TensorFlow, JAX).
- AGI Knowledge: Demonstrated understanding of transformer architectures, reinforcement learning, and meta-learning algorithms.
- Leadership: Proven track record of leading engineering teams through complex, ambiguous projects.
- Problem Solving: Exceptional ability to troubleshoot complex system bottlenecks and optimize computational efficiency.