Job Description
We are on a mission to define the technological landscape of 2026 and beyond. Nexus Horizon Technologies is seeking a visionary Senior AI Architect to lead the development of next-generation Generative AI systems. In this pivotal role, you will not just build models; you will architect the future infrastructure of intelligent automation.
As we approach the 2026 horizon, we need a technical leader who can bridge the gap between theoretical research and scalable production engineering. You will work alongside world-class researchers and engineers to deploy systems that are ethical, efficient, and transformative. If you are passionate about the future of AI and want to leave a lasting legacy in the industry, we want to hear from you.
Why join Nexus Horizon?
- Work on cutting-edge LLMs and Agentic AI workflows.
- Competitive compensation package with equity options.
- Flexible remote-first culture with a hub in Austin.
Responsibilities
- Design and implement scalable machine learning pipelines capable of handling petabyte-scale data for 2026 workloads.
- Lead the research and fine-tuning of Large Language Models (LLMs) to optimize for specific enterprise use cases.
- Architect 'Agentic AI' systems that autonomously execute complex multi-step workflows.
- Ensure model interpretability, fairness, and robustness in production environments.
- Collaborate with cross-functional teams to integrate AI capabilities into consumer-facing products.
- Mentor junior engineers and data scientists, fostering a culture of continuous learning.
- Stay ahead of the curve on emerging AI trends, particularly those predicted to define the 2026 landscape.
Qualifications
- Master’s degree or Ph.D. in Computer Science, Mathematics, or a related field.
- 5+ years of experience in Machine Learning, Deep Learning, or AI Engineering.
- Proficiency in Python and deep frameworks such as PyTorch or TensorFlow.
- Extensive experience with LLMs (GPT, LLaMA, etc.) and RAG (Retrieval-Augmented Generation) architectures.
- Strong understanding of MLOps practices, CI/CD pipelines, and cloud infrastructure (AWS/GCP).
- Experience deploying models to production with high availability and low latency.
- Proven track record of leading technical projects from conception to deployment.