Job Description
Shape the Future of Intelligence
Nexus Horizon Systems is at the forefront of defining the technological landscape for 2026 and beyond. We are seeking a visionary Senior AI Architect to lead the development of next-generation generative models and autonomous systems. In this role, you will not just write code; you will architect the neural pathways that define how machines think, learn, and interact with the world.
As a pioneer in the field, you will collaborate with cross-functional teams of quantum engineers, data scientists, and product strategists to build scalable, ethical, and robust AI solutions.
Responsibilities
- Design and deploy scalable AI/ML infrastructure capable of handling petabyte-scale datasets for 2026 workloads.
- Lead the architectural vision for Generative AI models, including LLMs and diffusion models.
- Mentor and guide a team of junior engineers and data scientists, fostering a culture of innovation and technical excellence.
- Define technical roadmaps and ensure alignment with long-term business objectives and ethical AI guidelines.
- Conduct research and prototype novel algorithms to stay ahead of industry trends in quantum computing and edge AI.
- Optimize model inference latency and reduce computational costs through advanced hardware/software co-design.
Qualifications
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field; PhD preferred.
- 10+ years of experience in software engineering and machine learning, with at least 4 years in a senior or lead architectural role.
- Deep expertise in Python, PyTorch, TensorFlow, and modern Deep Learning frameworks.
- Proven experience designing and deploying Large Language Models (LLMs) and Transformer architectures.
- Strong understanding of distributed systems, cloud architecture (AWS/Azure/GCP), and containerization (Docker/Kubernetes).
- Experience with MLOps pipelines, model versioning, and automated deployment strategies.
- Excellent problem-solving skills and the ability to communicate complex technical concepts to non-technical stakeholders.