Job Description
The Future of Intelligence Starts Here.
Nexus Horizon Systems is at the forefront of the 2026 technological revolution. We are seeking a visionary Senior AI Architect to spearhead our roadmap and define the infrastructure that will power the next generation of human-machine interaction.
In this role, you will not just write code; you will architect the very fabric of our 2026 strategy. You will bridge the gap between theoretical AI research and scalable production systems, ensuring our platform remains at the bleeding edge of Generative AI, Large Language Models (LLMs), and Autonomous Agents.
Why Join Us?
- Impact: Directly influence the strategic direction of our technology for the 2026 horizon.
- Autonomy: Work in a high-ownership environment where your ideas drive product evolution.
- Culture: A diverse team of engineers, researchers, and futurists pushing boundaries.
The Role:
We are looking for a leader who thrives on complexity and possesses a deep understanding of the AI landscape. You will lead a cross-functional team to build robust, secure, and scalable AI systems.
Responsibilities
- Define and execute the 2026 Technical Roadmap for AI infrastructure, identifying emerging trends in Quantum Computing and Neural Interfaces.
- Architect scalable microservices using Python, TensorFlow, and PyTorch to support high-volume AI inference.
- Lead the design of our proprietary LLM fine-tuning pipelines and Retrieval-Augmented Generation (RAG) frameworks.
- Mentor senior engineers and conduct technical reviews to ensure code quality and architectural integrity.
- Collaborate with product managers to translate strategic 2026 goals into technical specifications.
- Optimize model performance and reduce latency for real-time AI applications.
Qualifications
- 10+ years of experience in software engineering with a deep specialization in Machine Learning and Artificial Intelligence.
- Proven experience deploying large-scale production AI models, specifically in Generative AI or NLP.
- Expert proficiency in Python, C++, and cloud platforms (AWS, GCP, or Azure).
- Strong understanding of Deep Learning architectures (Transformers, GANs, Diffusion Models).
- Experience with MLOps, Kubernetes, and Docker for model deployment and scaling.
- Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.