Job Description
Nexus Horizon is at the forefront of defining the technological landscape for the year 2026. We are seeking a visionary Senior AI Architect to spearhead the development of next-generation agentic systems and multimodal Large Language Models. You will not just be building software; you will be architecting the infrastructure that will power the autonomous enterprises of the future.
In this role, you will bridge the gap between theoretical AI research and scalable production deployment. You will lead a team of elite engineers in deploying neuromorphic computing solutions and optimizing edge AI models for real-time decision-making. If you are passionate about the trajectory of AI and want to leave a legacy in the code that runs tomorrow, we want to hear from you.
Why Join Us?
- Work on the 2026 Tech Stack before it becomes standard.
- Competitive equity package and performance bonuses.
- Flexible remote-first policy with premium San Francisco HQ access.
- Access to cutting-edge GPU clusters and research grants.
Responsibilities
- Architect and deploy scalable, fault-tolerant AI infrastructures using Python, Rust, and Go.
- Lead the research and implementation of Agentic AI workflows and autonomous agents.
- Optimize Large Language Models (LLMs) for latency and throughput using quantization and distillation techniques.
- Collaborate with data scientists to fine-tune models on proprietary datasets for niche applications.
- Establish best practices for MLOps, CI/CD pipelines, and model monitoring.
- Guide the technical vision for the 2026 roadmap, ensuring alignment with business goals.
Qualifications
- Master’s or PhD in Computer Science, Artificial Intelligence, or a related quantitative field.
- Minimum 5+ years of experience in designing large-scale distributed systems and AI platforms.
- Deep expertise in PyTorch, TensorFlow, or JAX frameworks.
- Proven track record of deploying production-ready NLP and computer vision models.
- Experience with Kubernetes, Docker, and cloud platforms (AWS/GCP/Azure).
- Strong understanding of ethical AI, bias mitigation, and responsible machine learning.