Job Description
Build the Future of AI in 2026
We are seeking a visionary Senior AI Architect to lead the development of our predictive neural infrastructure. At Nexus Horizon Systems, we are not just building software for today; we are engineering the intelligent systems that will define the era of 2026. You will be at the forefront of ethical AI, quantum-ready algorithms, and autonomous decision-making frameworks.
Why Join Us?
- Work on projects that scale to global impact.
- Competitive compensation package and equity options.
- State-of-the-art facilities in the heart of San Francisco.
Role Overview
As a Senior AI Architect, you will design the core architecture for our next-generation generative models. You will bridge the gap between theoretical research and production-grade deployment, ensuring our systems are robust, scalable, and aligned with the emerging standards of 2026.
Responsibilities
- Architectural Design: Design scalable, fault-tolerant AI systems specifically optimized for the 2026 computing landscape, including quantum-hybrid environments.
- Model Optimization: Lead the optimization of Large Language Models (LLMs) and computer vision systems for low-latency, high-throughput deployment.
- Ethical AI Governance: Implement rigorous safety protocols and bias mitigation strategies to ensure AI deployment adheres to global compliance standards.
- System Integration: Integrate AI agents with legacy enterprise infrastructure, ensuring seamless interoperability.
- Trend Analysis: Monitor emerging AI trends, including neuromorphic computing, to advise leadership on long-term strategic roadmaps.
- Team Leadership: Mentor junior engineers and data scientists, fostering a culture of innovation and technical excellence.
Qualifications
- Education: Master’s or PhD in Computer Science, Artificial Intelligence, or a related technical field (PhD preferred).
- Experience: Minimum of 7+ years of experience in software engineering, with at least 4 years focused specifically on AI/ML architecture.
- Technical Skills: Proficiency in Python, TensorFlow, PyTorch, and distributed computing systems (Kubernetes, Docker).
- Domain Knowledge: Deep understanding of neural networks, NLP, and reinforcement learning paradigms.
- Problem Solving: Proven track record of solving complex scalability and optimization challenges.
- Communication: Excellent verbal and written communication skills, capable of articulating complex technical concepts to non-technical stakeholders.