Job Description
Are you ready to architect the intelligence of tomorrow? Nexus Horizon Labs is seeking a visionary Senior AI Architect to lead the development of our flagship 2026 AI Initiative. In this pivotal role, you will push the boundaries of Generative AI and Agentic Systems, building the infrastructure required for the next generation of Artificial General Intelligence (AGI).
As we look toward 2026, the landscape of AI is shifting from mere generation to autonomous reasoning. We are building a team of elite engineers who are not just using AI, but defining how it evolves. You will work on cutting-edge models, ensuring they are scalable, safe, and incredibly efficient. This is not just a job; it is a mission to define the future of human-computer interaction.
Why Join Us?
- Work on the core infrastructure powering the next decade of AI innovation.
- Competitive equity package and top-tier compensation.
- Remote-first culture with high-trust autonomy.
Responsibilities
- Architect and optimize large-scale inference pipelines for next-generation Large Language Models (LLMs).
- Research and implement novel techniques in model quantization and distillation to reduce latency.
- Lead the integration of Agentic Workflows into our production environments, enabling autonomous task completion.
- Collaborate with researchers to define the roadmap for our 2026 AI capabilities, focusing on safety and alignment.
- Design fault-tolerant distributed systems capable of handling petabyte-scale data streams.
- Mentor junior engineers and foster a culture of technical excellence and innovation.
Qualifications
- Ph.D. or Master’s degree in Computer Science, Machine Learning, or a related field.
- 5+ years of professional experience building, deploying, and scaling AI/ML systems at a production level.
- Deep expertise in PyTorch, TensorFlow, or JAX.
- Proven track record of working with state-of-the-art models (e.g., GPT-4, Claude, Llama 3).
- Strong understanding of distributed computing principles and cloud infrastructure (AWS, GCP, or Azure).
- Experience with reinforcement learning from human feedback (RLHF) and AI safety protocols.